Publications

Publications from members of the group #

2021
  1. PCPATCH: software for the topological construction of multigrid relaxation methods
    Patrick E. Farrell, Matthew G. Knepley, Lawrence Mitchell, and Florian Wechsung
    ACM Transactions on Mathematical Software
    To appear
    arxiv:1912.08516
    @article{Farrell:2021b,
      author        = {Patrick E. Farrell and Matthew G. Knepley and Lawrence Mitchell and Florian Wechsung},
      title         = {{PCPATCH: software for the topological construction of multigrid relaxation methods}},
      journal       = {ACM Transactions on Mathematical Software},
      year          = {2021},
      archiveprefix = {arXiv},
      eprint        = {1912.08516},
      primaryclass  = {cs.MS},
      note          = {To appear}
    }
    
  2. A Reynolds-robust preconditioner for the Reynolds-robust Scott–Vogelius discretization of the stationary incompressible Navier–Stokes equations
    Patrick E. Farrell, Lawrence Mitchell, L. Ridgway Scott, and Florian Wechsung
    SMAI Journal of Computational Mathematics
    To appear
    arxiv:2004.09398
    @article{Farrell:2021a,
      author        = {Patrick E. Farrell and Lawrence Mitchell and L. Ridgway Scott and Florian Wechsung},
      title         = {{A Reynolds-robust preconditioner for the Reynolds-robust Scott--Vogelius discretization of the stationary incompressible Navier--Stokes equations}},
      journal       = {SMAI Journal of Computational Mathematics},
      year          = {2021},
      archiveprefix = {arXiv},
      eprint        = {2004.09398},
      primaryclass  = {math.NA},
      note          = {To appear}
    }
    
2020
  1. A study of vectorization for matrix-free finite element methods
    Tianjiao Sun, Lawrence Mitchell, Kaushik Kulkarni, Andreas Klöckner, David A. Ham, and Paul H. J. Kelly
    International Journal of High Performance Computing Applications
    doi arxiv:1903.08243
    @article{Sun:2020,
      author        = {Tianjiao Sun and Lawrence Mitchell and Kaushik Kulkarni and Andreas Klöckner and David A. Ham and Paul H. J. Kelly},
      title         = {{A study of vectorization for matrix-free finite element methods}},
      journal       = {International Journal of High Performance Computing
    Applications},
      year          = {2020},
      pages         = {1--16},
      doi           = {10.1177/1094342020945005},
      archiveprefix = {arXiv},
      eprint        = {1903.08243},
      primaryclass  = {cs.MS}
    }
    
  2. Slate: extending Firedrake’s domain-specific abstraction to hybridized solvers for geoscience and beyond
    Thomas H. Gibson, Lawrence Mitchell, David A. Ham, and Colin J. Cotter
    Geoscientific Model Development
    doi arxiv:1802.00303
    @article{Gibson:2020,
      author        = {Thomas H. Gibson and Lawrence Mitchell and David A. Ham and Colin J. Cotter},
      title         = {{Slate: extending Firedrake's domain-specific abstraction to hybridized solvers for geoscience and beyond}},
      journal       = {Geoscientific Model Development},
      year          = {2020},
      volume        = {13},
      pages         = {735--761},
      doi           = {10.5194/gmd-13-735-2020},
      archiveprefix = {arXiv},
      eprint        = {1802.00303},
      primaryclass  = {cs.MS}
    }
    
  3. Real Time Fencing Move Classification and Detection at Touch Time during a Fencing Match
    Sunal, Cem Ekin, Willcocks, Chris G., and Obara, Boguslaw
    in Proc. Int. Conf. Pattern Recognition
    To appear
    @inproceedings{sunal20rtfencing,
      author    = {Sunal, Cem Ekin and Willcocks, Chris G. and Obara, Boguslaw},
      title     = {{Real Time Fencing Move Classification and Detection at Touch Time during a Fencing Match}},
      booktitle = {Proc. Int. Conf. Pattern Recognition},
      year      = {2020},
      publisher = {IEEE},
      note      = {To appear},
      category  = {surveillance imageclass},
      keywords  = {Conference},
      month     = {October}
    }
    
  4. Data Augmentation via Mixed Class Interpolation using Cycle-Consistent Generative Adversarial Networks Applied to Cross-Domain Imagery
    Sasaki, H., Willcocks, C.G., and Breckon, T.P.
    in Proc. Int. Conf. Pattern Recognition
    @inproceedings{sasaki20augmentation,
      author    = {Sasaki, H. and Willcocks, C.G. and Breckon, T.P.},
      title     = {{Data Augmentation via Mixed Class Interpolation using Cycle-Consistent Generative Adversarial Networks Applied to Cross-Domain Imagery}},
      booktitle = {Proc. Int. Conf. Pattern Recognition},
      year      = {2020},
      publisher = {IEEE},
      arxiv     = {https://arxiv.org/abs/2005.02436},
      category  = {surveillance imageclass},
      keywords  = {Conference},
      month     = {October},
      url       = {http://breckon.org/toby/publications/papers/sasaki20augmentation.pdf}
    }
    
  5. Lightweight task offloading exploiting MPI wait times for parallel adaptive mesh refinement
    Samfass, Philipp, Weinzierl, Tobias, Charrier, Dominic E., and Bader, Michael
    Concurrency and Computation: Practice and Experience
    doi
    @article{Samfass:2020:LoadBalancing,
      author    = {Samfass, Philipp and Weinzierl, Tobias and Charrier, Dominic E. and Bader, Michael},
      title     = {{Lightweight task offloading exploiting MPI wait times for parallel adaptive mesh refinement}},
      journal   = {Concurrency and Computation: Practice and Experience},
      year      = {2020},
      volume    = {32},
      number    = {24},
      pages     = {e5916},
      doi       = {https://doi.org/10.1002/cpe.5916}
    }
    
  6. TeaMPI–-Replication-Based Resilience Without the (Performance) Pain
    Samfass, Philipp, Weinzierl, Tobias, Hazelwood, Benjamin, and Bader, Michael
    in High Performance Computing
    @inproceedings{Samfass:2020:teaMPI,
      author    = {Samfass, Philipp and Weinzierl, Tobias and Hazelwood, Benjamin and Bader, Michael},
      title     = {{TeaMPI---Replication-Based Resilience Without the (Performance) Pain}},
      booktitle = {High Performance Computing},
      year      = {2020},
      pages     = {455--473},
      publisher = {Springer International Publishing},
      editor    = {Sadayappan, Ponnuswamy
    and Chamberlain, Bradford L.
    and Juckeland, Guido
    and Ltaief, Hatem}
    }
    
  7. Computer Vision for Protein-protein Docking
    Rudden, Lucas SP, Degiacomi, Matteo T, and Willcocks, Chris G
    Biophysical Journal
    doi
    @article{rudden2020computer,
      author    = {Rudden, Lucas SP and Degiacomi, Matteo T and Willcocks, Chris G},
      title     = {{Computer Vision for Protein-protein Docking}},
      journal   = {Biophysical Journal},
      year      = {2020},
      volume    = {118},
      number    = {3},
      pages     = {305a--306a},
      doi       = {10.1016/j.bpj.2019.11.1728},
      publisher = {Elsevier},
      keywords  = {Conference}
    }
    
  8. Robust multigrid methods for nearly incompressible elasticity using macro elements
    Patrick E. Farrell, Lawrence Mitchell, L. Ridgway Scott, and Florian Wechsung
    Submitted to SIAM Journal on Numerical Analysis
    arxiv:2002.02051
    @misc{Farrell:2020,
      author        = {Patrick E. Farrell and Lawrence Mitchell and L. Ridgway Scott and Florian Wechsung},
      title         = {{Robust multigrid methods for nearly incompressible elasticity using macro elements}},
      year          = {2020},
      archiveprefix = {arXiv},
      eprint        = {2002.02051},
      primaryclass  = {math.NA},
      note          = {Submitted to SIAM Journal on Numerical Analysis}
    }
    
  9. Unsupervised Region-based Anomaly Detection in Brain MRI with Adversarial Image Inpainting
    Nguyen, Bao, Feldman, Adam, Bethapudi, Sarath, Jennings, Andrew, and Willcocks, Chris G
    arXiv preprint arXiv:2010.01942
    @article{nguyen2020unsupervised,
      author    = {Nguyen, Bao and Feldman, Adam and Bethapudi, Sarath and Jennings, Andrew and Willcocks, Chris G},
      title     = {{Unsupervised Region-based Anomaly Detection in Brain MRI with Adversarial Image Inpainting}},
      journal   = {arXiv preprint arXiv:2010.01942},
      year      = {2020},
      keywords  = {Preprint},
      url       = {https://arxiv.org/abs/2010.01942}
    }
    
  10. Delayed approximate matrix assembly in multigrid with dynamic precisions
    Murray, Charles D. and Weinzierl, Tobias
    Concurrency and Computation: Practice and Experience
    doi
    @article{Murray:2020:Delayed,
      author    = {Murray, Charles D. and Weinzierl, Tobias},
      title     = {{Delayed approximate matrix assembly in multigrid with dynamic precisions}},
      journal   = {Concurrency and Computation: Practice and Experience},
      year      = {2020},
      volume    = {n/a},
      number    = {n/a},
      pages     = {e5941},
      doi       = {https://doi.org/10.1002/cpe.5941}
    }
    
  11. Stabilized asynchronous fast adaptive composite multigrid using additive damping
    Murray, Charles D. and Weinzierl, Tobias
    Numerical Linear Algebra with Applications
    doi
    @article{Murray:2020:adaFACx,
      author    = {Murray, Charles D. and Weinzierl, Tobias},
      title     = {{Stabilized asynchronous fast adaptive composite multigrid using additive damping}},
      journal   = {Numerical Linear Algebra with Applications},
      year      = {2020},
      volume    = {n/a},
      number    = {n/a},
      pages     = {e2328},
      doi       = {https://doi.org/10.1002/nla.2328}
    }
    
  12. Segmentation of Macular Edema Datasets with Small Residual 3D U-Net Architectures
    Jonathan Frawley, Chris G. Willcocks, Maged Habib, Caspar Geenen, David H. Steel, and Boguslaw Obara
    arXiv preprint arXiv:2005.04697
    @article{frawley2020segmentation,
      author    = {Jonathan Frawley and Chris G. Willcocks and Maged Habib and Caspar Geenen and David H. Steel and Boguslaw Obara},
      title     = {{Segmentation of Macular Edema Datasets with Small Residual 3D U-Net Architectures}},
      journal   = {arXiv preprint arXiv:2005.04697},
      year      = {2020},
      keywords  = {Preprint},
      url       = {https://arxiv.org/abs/2005.04697}
    }
    
  13. Vectorization and Minimization of Memory Footprint for Linear High-Order Discontinuous Galerkin Schemes
    Jean-Matthieu Gallard, Leonhard Rannabauer, Anne Reinarz, and Michael Bader
    in PDSEC
    @inproceedings{Gallard2020,
      author    = {Jean-Matthieu Gallard and  Leonhard Rannabauer and  Anne Reinarz and  Michael Bader},
      title     = {{Vectorization and Minimization of Memory Footprint for Linear High-Order Discontinuous Galerkin Schemes}},
      booktitle = {PDSEC},
      year      = {2020},
      address   = {Denver},
      language  = {en},
      month     = {Feb}
    }
    
  14. Multi-view Object Detection Using Epipolar Constraints within Cluttered X-ray Security Imagery
    Isaac-Medina, B.K.S., Willcocks, C.G., and Breckon, T.P.
    in Proc. Int. Conf. Pattern Recognition
    @inproceedings{isaac20multiview,
      author    = {Isaac-Medina, B.K.S. and Willcocks, C.G. and Breckon, T.P.},
      title     = {{Multi-view Object Detection Using Epipolar Constraints within Cluttered X-ray Security Imagery}},
      booktitle = {Proc. Int. Conf. Pattern Recognition},
      year      = {2020},
      publisher = {IEEE},
      category  = {baggage},
      keywords  = {Conference},
      month     = {October},
      url       = {http://breckon.org/toby/publications/papers/isaac20multiview.pdf}
    }
    
  15. Enclave Tasking for DG Methods on Dynamically Adaptive Meshes
    Charrier, Dominic Etienne, Hazelwood, Benjamin, and Weinzierl, Tobias
    SIAM Journal on Scientific Computing
    doi
    @article{Charrier:2020:EnclaveTasking,
      author    = {Charrier, Dominic Etienne and Hazelwood, Benjamin and Weinzierl, Tobias},
      title     = {{Enclave Tasking for DG Methods on Dynamically Adaptive Meshes}},
      journal   = {SIAM Journal on Scientific Computing},
      year      = {2020},
      volume    = {42},
      number    = {3},
      pages     = {C69--C96},
      doi       = {10.1137/19M1276194}
    }
    
  16. Gradient Origin Networks
    Bond-Taylor, Sam and Willcocks, Chris G
    arXiv preprint arXiv:2007.02798
    @article{bond2020gradient,
      author    = {Bond-Taylor, Sam and Willcocks, Chris G},
      title     = {{Gradient Origin Networks}},
      journal   = {arXiv preprint arXiv:2007.02798},
      year      = {2020},
      keywords  = {Preprint},
      url       = {https://arxiv.org/abs/2007.02798}
    }
    
  17. ExaHyPE: An engine for parallel dynamically adaptive simulations of wave problems
    Anne Reinarz, Dominic E. Charrier, Michael Bader, Luke Bovard, Michael Dumbser, Kenneth Duru, Francesco Fambri, Alice-Agnes Gabriel, Jean-Matthieu Gallard, Sven Köppel, Lukas Krenz, Leonhard Rannabauer, Luciano Rezzolla, Philipp Samfass, Maurizio Tavelli, and Tobias Weinzierl
    Computer Physics Communications
    doi
    @article{Reinarz:2020:ExaHyPE,
      author    = {Anne Reinarz and Dominic E. Charrier and Michael Bader and Luke Bovard and Michael Dumbser and Kenneth Duru and Francesco Fambri and Alice-Agnes Gabriel and Jean-Matthieu Gallard and Sven Köppel and Lukas Krenz and Leonhard Rannabauer and Luciano Rezzolla and Philipp Samfass and Maurizio Tavelli and Tobias Weinzierl},
      title     = {{ExaHyPE: An engine for parallel dynamically adaptive simulations of wave problems}},
      journal   = {Computer Physics Communications},
      year      = {2020},
      volume    = {254},
      pages     = {107251},
      doi       = {https://doi.org/10.1016/j.cpc.2020.107251}
    }
    
  18. The relationship between curvilinear structure enhancement and ridge detection methods
    Alhasson, Haifa F., Willcocks, Chris G., Alharbi, Shuaa S., Kasim, Adetayo, and Obara, Boguslaw
    The Visual Computer
    doi
    @article{alhasson2020relationship,
      author    = {Alhasson, Haifa F. and Willcocks, Chris G. and Alharbi, Shuaa S. and Kasim, Adetayo and Obara, Boguslaw},
      title     = {{The relationship between curvilinear structure enhancement and ridge detection methods}},
      journal   = {The Visual Computer},
      year      = {2020},
      doi       = {10.1007/s00371-020-01985-4},
      day       = {22},
      issn      = {1432-2315},
      keywords  = {Journal},
      month     = {Oct}
    }
    
2019
  1. The Peano Software—Parallel, Automaton-Based, Dynamically Adaptive Grid Traversals
    Weinzierl, Tobias
    ACM Trans. Math. Softw.
    doi
    @article{Weinzierl:2019:Peano,
      author    = {Weinzierl, Tobias},
      title     = {{The Peano Software—Parallel, Automaton-Based, Dynamically Adaptive Grid Traversals}},
      journal   = {ACM Trans. Math. Softw.},
      year      = {2019},
      volume    = {45},
      number    = {2},
      doi       = {10.1145/3319797},
      publisher = {Association for Computing Machinery},
      articleno = {14},
      numpages  = {41}
    }
    
  2. Compatible finite element methods for geophysical flows: automation and implementation using Firedrake
    Thomas H. Gibson, Andrew T. T. McRae, Colin J. Cotter, Lawrence Mitchell, and David A. Ham
    SpringerBriefs in Mathematics of Planet Earth
    doi
    @book{Gibson:2019,
      author    = {Thomas H. Gibson and Andrew T. T. McRae and Colin J. Cotter and Lawrence Mitchell and David A. Ham},
      title     = {{Compatible finite element methods for geophysical flows: automation and implementation using Firedrake}},
      year      = {2019},
      doi       = {10.1007/978-3-030-23957-2},
      series    = {SpringerBriefs in Mathematics of Planet Earth},
      publisher = {Springer}
    }
    
  3. Code generation for generally mapped finite elements
    Robert C. Kirby and Lawrence Mitchell
    ACM Transactions on Mathematical Software
    doi arxiv:1808.05513
    @article{Kirby:2019,
      author        = {Robert C. Kirby and Lawrence Mitchell},
      title         = {{Code generation for generally mapped finite elements}},
      journal       = {ACM Transactions on Mathematical Software},
      year          = {2019},
      volume        = {45},
      number        = {41},
      pages         = {41:1--41:23},
      doi           = {10.1145/3361745},
      archiveprefix = {arXiv},
      eprint        = {1808.05513},
      primaryclass  = {cs.MS}
    }
    
  4. Learning protein conformational space by enforcing physics with convolutions and latent interpolations
    Ramaswamy, Venkata K, Willcocks, Chris G, and Degiacomi, Matteo T
    arXiv preprint arXiv:1910.04543
    @article{ramaswamy2019learning,
      author    = {Ramaswamy, Venkata K and Willcocks, Chris G and Degiacomi, Matteo T},
      title     = {{Learning protein conformational space by enforcing physics with convolutions and latent interpolations}},
      journal   = {arXiv preprint arXiv:1910.04543},
      year      = {2019},
      keywords  = {Preprint},
      month     = {10},
      url       = {https://arxiv.org/abs/1910.04543}
    }
    
  5. High-performance dune modules for solving large-scale, strongly anisotropic elliptic problems with applications to aerospace composites
    R. Butler, T. Dodwell, A. Reinarz, A. Sandhu, R. Scheichl, and L. Seelinger
    Computer Physics Communications
    doi
    @article{Butler2019,
      author    = {R. Butler and T. Dodwell and A. Reinarz and A. Sandhu and R. Scheichl and L. Seelinger},
      title     = {{High-performance dune modules for solving large-scale, strongly anisotropic elliptic problems with applications to aerospace composites}},
      journal   = {Computer Physics Communications},
      year      = {2019},
      doi       = {https://doi.org/10.1016/j.cpc.2019.106997},
      abstract  = {The key innovation in this paper is an open-source, high-performance iterative solver for high contrast, strongly anisotropic elliptic partial differential equations implemented within dune-pdelab. The iterative solver exploits a robust, scalable two-level additive Schwarz preconditioner, GenEO (Spillane et al., 2014). The development of this solver has been motivated by the need to overcome the limitations of commercially available modelling tools for solving structural analysis simulations in aerospace composite applications. Our software toolbox dune-composites encapsulates the mathematical complexities of the underlying packages within an efficient C++ framework, providing an application interface to our new high-performance solver. We illustrate its use on a range of industrially motivated examples, which should enable other scientists to build on and extend dune-composites and the GenEO preconditioner for use in their own applications. We demonstrate the scalability of the solver on more than 15,000 cores of the UK national supercomputer Archer, solving an aerospace composite problem with over 200 million degrees of freedom in a few minutes. This scale of computation brings composites problems that would otherwise be unthinkable into the feasible range. To demonstrate the wider applicability of the new solver, we also confirm the robustness and scalability of the solver on SPE10, a challenging benchmark in subsurface flow/reservoir simulation.
    Program summary
    Program Title: dune-composites Program Files doi: http://dx.doi.org/10.17632/96mtdcmjsb.1 Licensing provisions: BSD 3-clause Programming language: C++ Nature of problem: dune-composites is designed to solve anisotropic linear elasticity equations for anisotropic, heterogeneous materials, e.g. composite materials. To achieve this, our contribution also implements a new preconditioner in dune-pdelab. Solution method: The anisotropic elliptic partial differential equations are solved via the finite element method. The resulting linear system is solved via an iterative solver with a robust, scalable two-level overlapping Schwarz preconditioner: GenEO.},
      issn      = {0010-4655},
      keywords  = {Composites, Parallel iterative solvers, Domain decomposition, High performance computing},
      url       = {http://www.sciencedirect.com/science/article/pii/S0010465519303364}
    }
    
  6. An augmented Lagrangian preconditioner for the 3D stationary incompressible Navier–Stokes equations at high Reynolds number
    Patrick E. Farrell, Lawrence Mitchell, and Florian Wechsung
    SIAM Journal on Scientific Computing
    doi arxiv:1810.03315
    @article{Farrell:2019,
      author        = {Patrick E. Farrell and Lawrence Mitchell and Florian Wechsung},
      title         = {{An augmented Lagrangian preconditioner for the 3D stationary incompressible Navier--Stokes equations at high Reynolds number}},
      journal       = {SIAM Journal on Scientific Computing},
      year          = {2019},
      volume        = {41},
      number        = {5},
      pages         = {A3073--A3096},
      doi           = {10.1137/18M1219370},
      archiveprefix = {arXiv},
      eprint        = {1810.03315},
      primaryclass  = {math.NA}
    }
    
  7. On GLM curl cleaning for a first order reduction of the CCZ4 formulation of the Einstein field equations
    Michael Dumbser, Francesco Fambri, Elena Gaburro, and Anne Reinarz
    Journal of Computational Physics
    doi
    @article{Dumbser2019,
      author    = {Michael Dumbser and Francesco Fambri and Elena Gaburro and Anne Reinarz},
      title     = {{On GLM curl cleaning for a first order reduction of the CCZ4 formulation of the Einstein field equations}},
      journal   = {Journal of Computational Physics},
      year      = {2019},
      doi       = {https://doi.org/10.1016/j.jcp.2019.109088},
      abstract  = {In this paper we propose an extension of the generalized Lagrangian multiplier method (GLM) of Munz et al. [52], [30], which was originally conceived for the numerical solution of the Maxwell and MHD equations with divergence-type involutions, to the case of hyperbolic PDE systems with curl-type involutions. The key idea here is to solve an augmented PDE system, in which curl errors propagate away via a Maxwell-type evolution system. The new approach is first presented on a simple model problem, in order to explain the basic ideas. Subsequently, we apply it to a strongly hyperbolic first order reduction of the CCZ4 formulation (FO-CCZ4) of the Einstein field equations of general relativity, which is endowed with 11 curl constraints. Several numerical examples, including the long-time evolution of a stable neutron star in anti-Cowling approximation, are presented in order to show the obtained improvements with respect to the standard formulation without special treatment of the curl involution constraints. The main advantages of the proposed GLM approach are its complete independence of the underlying numerical scheme and grid topology and its easy implementation into existing computer codes. However, this flexibility comes at the price of needing to add for each curl involution one additional 3 vector plus another scalar in the augmented system for homogeneous curl constraints, and even two additional scalars for non-homogeneous curl involutions. For the FO-CCZ4 system with 11 homogeneous curl involutions, this means that additional 44 evolution quantities need to be added.},
      issn      = {0021-9991},
      keywords  = {Generalized Lagrangian multiplier approach (GLM), Hyperbolic PDE systems with curl involutions, Einstein field equations with matter source terms, First order reduction of the CCZ4 system (FO-CCZ4), Stable neutron star in anti-Cowling approximation},
      url       = {http://www.sciencedirect.com/science/article/pii/S0021999119307934}
    }
    
  8. A simple diffuse interface approach on adaptive Cartesian grids for the linear elastic wave equations with complex topography
    Maurizio Tavelli, Michael Dumbser, Dominic Etienne Charrier, Leonhard Rannabauer, Tobias Weinzierl, and Michael Bader
    Journal of Computational Physics
    doi
    @article{Tavelli:2019:DiffusiveInterface,
      author    = {Maurizio Tavelli and Michael Dumbser and Dominic Etienne Charrier and Leonhard Rannabauer and Tobias Weinzierl and Michael Bader},
      title     = {{A simple diffuse interface approach on adaptive Cartesian grids for the linear elastic wave equations with complex topography}},
      journal   = {Journal of Computational Physics},
      year      = {2019},
      volume    = {386},
      pages     = {158--189},
      doi       = {https://doi.org/10.1016/j.jcp.2019.02.004}
    }
    
  9. A High-Performance Implementation of a Robust Preconditioner for Heterogeneous Problems
    Linus Seelinger, Anne Reinarz, and Robert Scheichl
    in PPAM 2019
    @inproceedings{Seelinger2019,
      author    = {Linus Seelinger and  Anne Reinarz and  Robert Scheichl},
      title     = {{A High-Performance Implementation of a Robust Preconditioner for Heterogeneous Problems}},
      booktitle = {PPAM 2019},
      year      = {2019},
      publisher = {Springer},
      address   = {Bialystok},
      language  = {en}
    }
    
  10. A multi-core ready discrete element method with triangles using dynamically adaptive multiscale grids
    Krestenitis, Konstantinos and Weinzierl, Tobias
    Concurrency and Computation: Practice and Experience
    doi
    @article{Krestenitis:2019:DEM,
      author    = {Krestenitis, Konstantinos and Weinzierl, Tobias},
      title     = {{A multi-core ready discrete element method with triangles using dynamically adaptive multiscale grids}},
      journal   = {Concurrency and Computation: Practice and Experience},
      year      = {2019},
      volume    = {31},
      number    = {19},
      pages     = {e4935},
      doi       = {https://doi.org/10.1002/cpe.4935}
    }
    
  11. Deep-learning based, automated segmentation of macular holes in optical coherence tomography
    Jonathan Frawley, Chris Willcocks, Habib Maged, Geenen Caspar, David Steel, and Boguslaw Obara
    in The Wolfson Research Institute for Health and Wellbeing Fourth Annual Early Career Researcher Conference
    @inproceedings{frawley2019deep,
      author    = {Jonathan Frawley and Chris Willcocks and Habib Maged and Geenen Caspar and David Steel and Boguslaw Obara},
      title     = {{Deep-learning based, automated segmentation of macular holes in optical coherence tomography}},
      booktitle = {The Wolfson Research Institute for Health and Wellbeing Fourth Annual Early Career Researcher Conference},
      year      = {2019},
      address   = {Durham, UK},
      keywords  = {Conference},
      month     = {6}
    }
    
  12. Role-Oriented Code Generation in an Engine for Solving Hyperbolic PDE Systems
    Jean-Matthieu Gallard, Lukas Krenz, Leonhard Rannabauer, Anne Reinarz, and Michael Bader
    in SC19 SE-HER
    @inproceedings{Gallard2019,
      author    = {Jean-Matthieu Gallard and  Lukas Krenz and  Leonhard Rannabauer and  Anne Reinarz and  Michael Bader},
      title     = {{Role-Oriented Code Generation in an Engine for Solving Hyperbolic PDE Systems}},
      booktitle = {SC19 SE-HER},
      year      = {2019},
      address   = {Denver},
      language  = {en},
      month     = {Nov}
    }
    
  13. Studies on the energy and deep memory behaviour of a cache-oblivious, task-based hyperbolic PDE solver
    Dominic E Charrier, Benjamin Hazelwood, Ekaterina Tutlyaeva, Michael Bader, Michael Dumbser, Andrey Kudryavtsev, Alexander Moskovsky, and Tobias Weinzierl
    The International Journal of High Performance Computing Applications
    doi
    @article{Charrier:2019:Energy,
      author    = {Dominic E Charrier and Benjamin Hazelwood and Ekaterina Tutlyaeva and Michael Bader and Michael Dumbser and Andrey Kudryavtsev and Alexander Moskovsky and Tobias Weinzierl},
      title     = {{Studies on the energy and deep memory behaviour of a cache-oblivious, task-based hyperbolic PDE solver}},
      journal   = {The International Journal of High Performance Computing Applications},
      year      = {2019},
      volume    = {33},
      number    = {5},
      pages     = {973--986},
      doi       = {10.1177/1094342019842645}
    }
    
  14. Automated shape differentiation in the Unified Form Language
    David A. Ham, Lawrence Mitchell, Alberto Paganini, and Florian Wechsung
    Structural and Multidisciplinary Optimization
    doi arxiv:1808.08083
    @article{Ham:2019,
      author        = {David A. Ham and Lawrence Mitchell and Alberto Paganini and Florian Wechsung},
      title         = {{Automated shape differentiation in the Unified Form Language}},
      journal       = {Structural and Multidisciplinary Optimization},
      year          = {2019},
      volume        = {60},
      pages         = {1813--1820},
      doi           = {10.1007/s00158-019-02281-z},
      archiveprefix = {arXiv},
      eprint        = {1808.08083},
      primaryclass  = {math.NA}
    }
    
  15. Sequential graph-based extraction of curvilinear structures
    Alharbi, Shuaa S., Willcocks, Chris G., Jackson, Philip T. G., Alhasson, Haifa F., and Obara, Boguslaw
    Signal, Image and Video Processing
    doi
    @article{alharbi2017sequential,
      author    = {Alharbi, Shuaa S. and Willcocks, Chris G. and Jackson, Philip T. G. and Alhasson, Haifa F. and Obara, Boguslaw},
      title     = {{Sequential graph-based extraction of curvilinear structures}},
      journal   = {Signal, Image and Video Processing},
      year      = {2019},
      volume    = {13},
      number    = {5},
      pages     = {941--949},
      doi       = {10.1007/s11760-019-01431-6},
      day       = {01},
      issn      = {1863-1711},
      keywords  = {Journal},
      month     = {Jul}
    }
    
  16. Sparse grid approximation spaces for space–time boundary integral formulations of the heat equation
    Alexey Chernov and Anne Reinarz
    Computers & Mathematics with Applications
    doi
    @article{Chernov2019,
      author    = {Alexey Chernov and Anne Reinarz},
      title     = {{Sparse grid approximation spaces for space–time boundary integral formulations of the heat equation}},
      journal   = {Computers & Mathematics with Applications},
      year      = {2019},
      volume    = {78},
      number    = {11},
      pages     = {3605--3619},
      doi       = {https://doi.org/10.1016/j.camwa.2019.06.036},
      issn      = {0898-1221},
      keywords  = {Boundary element methods, Space–time approximation, Parabolic problems, Sparse grids, Adaptive sparse grids},
      url       = {http://www.sciencedirect.com/science/article/pii/S0898122119304626}
    }
    
2018
  1. Thetis coastal ocean model: discontinuous Galerkin discretization for the three-dimensional hydrostatic equations
    Tuomas Kärnä, Stephan C. Kramer, Lawrence Mitchell, David A. Ham, Matthew D. Piggott, and António M. Baptista
    Geoscientific Model Development
    doi arxiv:1711.08552
    @article{Karna:2018,
      author        = {Tuomas Kärnä and Stephan C. Kramer and Lawrence Mitchell and David A. Ham and Matthew D. Piggott and António M. Baptista},
      title         = {{Thetis coastal ocean model: discontinuous Galerkin discretization for the three-dimensional hydrostatic equations}},
      journal       = {Geoscientific Model Development},
      year          = {2018},
      volume        = {11},
      number        = {11},
      pages         = {4359--4382},
      doi           = {10.5194/gmd-11-4359-2018},
      archiveprefix = {arXiv},
      eprint        = {1711.08552},
      primaryclass  = {physics.ao-ph}
    }
    
  2. A Case Study for a New Invasive Extension of Intel’s Threading Building Blocks
    Schreiber, Martin and Weinzierl, Tobias
    in Proceedings of the 3rd Workshop on Co-Scheduling of HPC Applications (COSH 2018)
    doi
    @inproceedings{Schreiber:2018:InvasicTBB,
      author    = {Schreiber, Martin and  Weinzierl, Tobias},
      title     = {{A Case Study for a New Invasive Extension of Intel’s Threading Building Blocks}},
      booktitle = {Proceedings of the 3rd Workshop on Co-Scheduling of HPC Applications (COSH 2018)},
      year      = {2018},
      doi       = {10.14459/2018md1428538},
      address   = {Manchester, United Kingdom},
      editor    = {Trinitis, Carsten and  Weidendorfer, Josef}
    }
    
  3. Using Deep Convolutional Neural Network Architectures for Object Classification and Detection Within X-Ray Baggage Security Imagery
    S. Akcay, M. E. Kundegorski, Chris G. Willcocks, and T. P. Breckon
    IEEE Transactions on Information Forensics and Security
    doi
    @article{ackay2017onusing,
      author    = {S. Akcay and M. E. Kundegorski and Chris G. Willcocks and T. P. Breckon},
      title     = {{Using Deep Convolutional Neural Network Architectures for Object Classification and Detection Within X-Ray Baggage Security Imagery}},
      journal   = {IEEE Transactions on Information Forensics and Security},
      year      = {2018},
      volume    = {13},
      number    = {9},
      pages     = {2203--2215},
      doi       = {10.1109/TIFS.2018.2812196},
      issn      = {1556-6013},
      keywords  = {Journal},
      month     = {9}
    }
    
  4. Solver composition across the PDE/linear algebra barrier
    Robert C. Kirby and Lawrence Mitchell
    SIAM Journal on Scientific Computing
    doi arxiv:1706.01346
    @article{Kirby:2018,
      author        = {Robert C. Kirby and Lawrence Mitchell},
      title         = {{Solver composition across the PDE/linear algebra barrier}},
      journal       = {SIAM Journal on Scientific Computing},
      year          = {2018},
      volume        = {40},
      number        = {1},
      pages         = {C76--C98},
      doi           = {10.1137/17M1133208},
      archiveprefix = {arXiv},
      eprint        = {1706.01346},
      primaryclass  = {cs.MS}
    }
    
  5. dune-composites - A New Framework for High-Performance Finite Element Modelling of Laminates
    Reinarz, Anne, Dodwell, Tim, Fletcher, Tim, Seelinger, Linus, Butler, Richard, and Scheichl, Robert
    Composite Structures
    doi
    @article{Reinarz2018,
      author    = {Reinarz, Anne and  Dodwell, Tim and  Fletcher, Tim and  Seelinger, Linus and  Butler, Richard and  Scheichl, Robert},
      title     = {{dune-composites - A New Framework for High-Performance Finite Element Modelling of Laminates}},
      journal   = {Composite Structures},
      year      = {2018},
      volume    = {184},
      pages     = {269--278},
      doi       = {10.1016/j.compstruct.2017.09.104},
      issn      = {0263-8223},
      month     = {Jan}
    }
    
  6. Influence of a-posteriori subcell limiting on fault frequency in higher-order DG schemes
    Reinarz, A., Gallard, J.-M., and Bader, M.
    Proceedings of FTXS 2018: 8th Workshop on Fault Tolerance for HPC at eXtreme Scale, Held in conjunction with SC18: The International Conference for High Performance Computing, Networking, Storage and Analysis
    @article{Reinarz2018FTXS,
      author    = {Reinarz, A. and Gallard, J.-M. and Bader, M.},
      title     = {{Influence of a-posteriori subcell limiting on fault frequency in higher-order DG schemes}},
      journal   = {Proceedings of FTXS 2018: 8th Workshop on Fault Tolerance for HPC at eXtreme Scale, 
    Held in conjunction with SC18: The International Conference for High Performance Computing, Networking, Storage and Analysis},
      year      = {2018},
      pages     = {79--86}
    }
    
  7. TSFC: a structure-preserving form compiler
    Miklós Homolya, Lawrence Mitchell, Fabio Luporini, and David A. Ham
    SIAM Journal on Scientific Computing
    doi arxiv:1705.03667
    @article{Homolya:2018,
      author        = {Miklós Homolya and Lawrence Mitchell and Fabio Luporini and David A. Ham},
      title         = {{TSFC: a structure-preserving form compiler}},
      journal       = {SIAM Journal on Scientific Computing},
      year          = {2018},
      volume        = {40},
      number        = {3},
      pages         = {C401--C428},
      doi           = {10.1137/17M1130642},
      archiveprefix = {arXiv},
      eprint        = {1705.03667},
      primaryclass  = {cs.MS}
    }
    
  8. Deep learning for the classification and clustering of museum collections
    Matthew Roberts, Chris Willcocks, Anna Leone, and Boguslaw Obara
    in Annual Meeting of the European Association of Archaeologists
    @inproceedings{roberts2018deep,
      author    = {Matthew Roberts and Chris Willcocks and Anna Leone and Boguslaw Obara},
      title     = {{Deep learning for the classification and clustering of museum collections}},
      booktitle = {Annual Meeting of the European Association of Archaeologists},
      year      = {2018},
      address   = {Barcelona, Spain},
      keywords  = {Conference},
      month     = {9}
    }
    
  9. Deep Learning for the Classification and Clustering of Museum Collections
    Matthew Roberts, Chris G. Willcocks, and Boguslaw Obara
    Computing Applications & Quantitative Methods in Archaeology
    @article{matt2017deep,
      author    = {Matthew Roberts and Chris G. Willcocks and Boguslaw Obara},
      title     = {{Deep Learning for the Classification and Clustering of Museum Collections}},
      journal   = {Computing Applications & Quantitative Methods in Archaeology},
      year      = {2018},
      keywords  = {Conference},
      month     = {11}
    }
    
  10. TMIXT: A process flow for Transcribing MIXed handwritten and machine-printed Text
    F. Medhat, M. Mohammadi, S. Jaf, C. G. Willcocks, T. P. Breckon, P. Matthews, A. S. McGough, G. Theodoropoulos, and B. Obara
    in 2018 IEEE International Conference on Big Data (Big Data)
    doi
    @inproceedings{medhat2018TMIXT,
      author    = {F. Medhat and M. Mohammadi and S. Jaf and C. G. Willcocks and T. P. Breckon and P. Matthews and A. S. McGough and G. Theodoropoulos and B. Obara},
      title     = {{TMIXT: A process flow for Transcribing MIXed handwritten and machine-printed Text}},
      booktitle = {2018 IEEE International Conference on Big Data (Big Data)},
      year      = {2018},
      volume    = {},
      number    = {},
      pages     = {2986--2994},
      doi       = {10.1109/BigData.2018.8622136},
      issn      = {},
      keywords  = {Conference},
      month     = {Dec}
    }
    
  11. Macular hole and edema segmentation with 3D image-to-image networks
    Chris G. Willcocks, Jonathan Frawley, Gregoire Payen de La Garanderie, Habib Maged, Geenen Caspar, David Steel, and Boguslaw Obara
    in International Society for Eye Research Conference
    @inproceedings{willcocks2018macular,
      author    = {Chris G. Willcocks and Jonathan Frawley and Gregoire Payen de La Garanderie and Habib Maged and Geenen Caspar and David Steel and Boguslaw Obara},
      title     = {{Macular hole and edema segmentation with 3D image-to-image networks}},
      booktitle = {International Society for Eye Research Conference},
      year      = {2018},
      address   = {Belfast, Northern Ireland, UK},
      keywords  = {Conference},
      month     = {9}
    }
    
  12. Multi-scale Segmentation and Surface Fitting for Measuring 3D Macular Holes
    A. V. Nasrulloh, C. G. Willcocks, P. T. G. Jackson, C. Geenen, M. S. Habib, D. H. W. Steel, and B. Obara
    IEEE Transactions on Medical Imaging
    doi
    @article{nasrulloh2017multiscale,
      author    = {A. V. Nasrulloh and C. G. Willcocks and P. T. G. Jackson and C. Geenen and M. S. Habib and D. H. W. Steel and B. Obara},
      title     = {{Multi-scale Segmentation and Surface Fitting for Measuring 3D Macular Holes}},
      journal   = {IEEE Transactions on Medical Imaging},
      year      = {2018},
      volume    = {37},
      pages     = {580--589},
      doi       = {10.1109/TMI.2017.2767908},
      issn      = {0278-0062},
      keywords  = {Journal},
      month     = {2}
    }
    
  13. A Bayesian framework for assessing the strength distribution of composite structures with random defects
    A. Sandhu, A. Reinarz, and T.J. Dodwell
    Composite Structures
    doi
    @article{Sandhu2018,
      author    = {A. Sandhu and A. Reinarz and T.J. Dodwell},
      title     = {{A Bayesian framework for assessing the strength distribution of composite structures with random defects}},
      journal   = {Composite Structures},
      year      = {2018},
      volume    = {205},
      pages     = {58--68},
      doi       = {https://doi.org/10.1016/j.compstruct.2018.08.074},
      abstract  = {This paper presents a novel stochastic framework to quantify the knock down in strength from out-of-plane wrinkles at the coupon level. The key innovation is a Markov Chain Monte Carlo algorithm which rigorously derives the stochastic distribution of wrinkle defects directly informed from image data of defects. The approach significantly reduces uncertainty in the parameterization of stochastic numerical studies on the effects of defects. To demonstrate our methodology, we present an original stochastic study to determine the distribution of strength of corner bend samples with random out-of-plane wrinkle defects. The defects are parameterized by stochastic random fields defined using Karhunen-Loéve (KL) modes. The distribution of KL coefficients are inferred from misalignment data extracted from B-Scan data using a modified version of Multiple Field Image Analysis. The strength distribution is estimated by embedding wrinkles into high fidelity FE simulations using the high performance toolbox dune-composites from which we observe severe knockdowns to 74% of structural strength with a probability of 1/200. Supported by the literature our results highlight the strong correlation between maximum misalignment and knockdown in coupon strength. This observation allows us to define a surrogate model providing fast assessment of predicted strength informed from stochastic simulations utilizing both observed wrinkle data and high fidelity finite element models.},
      issn      = {0263-8223},
      keywords  = {Markov Chain Monte Carlo, Wrinkle defects, Stochastic finite elements, Non-destructive testing},
      url       = {http://www.sciencedirect.com/science/article/pii/S0263822318314569}
    }
    
2017
  1. Multiscale Modelling of Lamination Defects in Curved Structures
    Reinarz, Anne, Fletcher, Tim, Dodwell, Tim, Butler, Richard, and Scheichl, Robert
    in 21st International Conference on Composite Materials
    @inproceedings{Reinarz2017,
      author    = {Reinarz, Anne and  Fletcher, Tim and  Dodwell, Tim and  Butler, Richard and  Scheichl, Robert},
      title     = {{Multiscale Modelling of Lamination Defects in Curved Structures}},
      booktitle = {21st International Conference on Composite Materials},
      year      = {2017},
      month     = {Sep}
    }
    
  2. Vertical slice modelling of nonlinear Eady waves using a compatible finite element method
    Hiroe Yamazaki, Jemma Shipton, Mike J. P. Cullen, Lawrence Mitchell, and Colin J. Cotter
    Journal of Computational Physics
    doi arxiv:1611.04929
    @article{Yamazaki:2017,
      author        = {Hiroe Yamazaki and Jemma Shipton and Mike J. P. Cullen and Lawrence Mitchell and Colin J. Cotter},
      title         = {{Vertical slice modelling of nonlinear Eady waves using a compatible finite element method}},
      journal       = {Journal of Computational Physics},
      year          = {2017},
      volume        = {343},
      pages         = {130--149},
      doi           = {10.1016/j.jcp.2017.04.006},
      archiveprefix = {arXiv},
      eprint        = {1611.04929},
      primaryclass  = {math.NA}
    }
    
  3. Extracting 3D Parametric Curves from 2D Images of Helical Objects
    Chris G. Willcocks, Philip T.G. Jackson, Carl J. Nelson, and Boguslaw Obara
    IEEE Transactions on Pattern Analysis and Machine Intelligence
    doi
    @article{willcocks2017extracting,
      author    = {Chris G. Willcocks and Philip T.G. Jackson and Carl J. Nelson and Boguslaw Obara},
      title     = {{Extracting 3D Parametric Curves from 2D Images of Helical Objects}},
      journal   = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
      year      = {2017},
      volume    = {39},
      number    = {9},
      pages     = {1757--1769},
      doi       = {10.1109/TPAMI.2016.2613866},
      issn      = {0162-8828},
      keywords  = {Journal},
      month     = {9}
    }
    
  4. Interactive GPU Active Contours for Segmenting Inhomogeneous Objects
    Chris G. Willcocks, Philip T.G. Jackson, Carl J. Nelson, Amar Nasrulloh, and Boguslaw Obara
    Journal of Real-time Image Processing
    video url: https://youtube.com/watch?v=6W4mO7BPeGg
    doi
    @article{willcocks2017interactive,
      author    = {Chris G. Willcocks and Philip T.G. Jackson and Carl J. Nelson and Amar Nasrulloh and Boguslaw Obara},
      title     = {{Interactive GPU Active Contours for Segmenting Inhomogeneous Objects}},
      journal   = {Journal of Real-time Image Processing},
      year      = {2017},
      doi       = {10.1007/s11554-017-0740-1},
      note      = {video url: https://youtube.com/watch?v=6W4mO7BPeGg},
      day       = {26},
      issn      = {1861-8219},
      keywords  = {Journal},
      month     = {12}
    }
    
2016
  1. Real-time segmentation of brain vasculature and identification of anomalies in magnetic resonance angiography
    Nitin Mukerji, Carl J. Nelson, Chris G. Willcocks, Philip T.G. Jackson, and Boguslaw Obara
    in European Congress of Neurosurgery
    @inproceedings{mukerji2016real,
      author    = {Nitin Mukerji and Carl J. Nelson and Chris G. Willcocks and Philip T.G. Jackson and Boguslaw Obara},
      title     = {{Real-time segmentation of brain vasculature and identification of anomalies in magnetic resonance angiography}},
      booktitle = {European Congress of Neurosurgery},
      year      = {2016},
      address   = {Athens, Greece},
      keywords  = {Conference},
      month     = {9}
    }
    
  2. Efficient mesh management in Firedrake using PETSc-DMPlex
    Michael Lange, Lawrence Mitchell, Matthew G. Knepley, and Gerard J. Gorman
    SIAM Journal on Scientific Computing
    doi arxiv:1506.07749
    @article{Lange:2016,
      author        = {Michael Lange and Lawrence Mitchell and Matthew G. Knepley and Gerard J. Gorman},
      title         = {{Efficient mesh management in Firedrake using PETSc-DMPlex}},
      journal       = {SIAM Journal on Scientific Computing},
      year          = {2016},
      volume        = {38},
      number        = {5},
      pages         = {S143--S155},
      doi           = {10.1137/15M1026092},
      archiveprefix = {arXiv},
      eprint        = {1506.07749},
      primaryclass  = {cs.MS}
    }
    
  3. High level implementation of geometric multigrid solvers for finite element problems: applications in atmospheric modelling
    Lawrence Mitchell and Eike Hermann Müller
    Journal of Computational Physics
    doi arxiv:1605.00492
    @article{Mitchell:2016,
      author        = {Lawrence Mitchell and Eike Hermann Müller},
      title         = {{High level implementation of geometric multigrid solvers for finite element problems: applications in atmospheric modelling}},
      journal       = {Journal of Computational Physics},
      year          = {2016},
      volume        = {327},
      pages         = {1--18},
      doi           = {10.1016/j.jcp.2016.09.037},
      archiveprefix = {arXiv},
      eprint        = {1605.00492},
      primaryclass  = {cs.MS}
    }
    
  4. A structure-exploiting numbering algorithm for finite elements on extruded meshes, and its performance evaluation in Firedrake
    Gheorghe-Teodor Bercea, Andrew T. T. McRae, David A. Ham, Lawrence Mitchell, Florian Rathgeber, Luigi Nardi, Fabio Luporini, and Paul H. J. Kelly
    Geoscientific Model Development
    doi arxiv:1604.05937
    @article{Bercea:2016,
      author        = {Gheorghe-Teodor Bercea and Andrew T. T. McRae and David A. Ham and Lawrence Mitchell and Florian Rathgeber and Luigi Nardi and Fabio Luporini and Paul H. J. Kelly},
      title         = {{A structure-exploiting numbering algorithm for finite elements on extruded meshes, and its performance evaluation in Firedrake}},
      journal       = {Geoscientific Model Development},
      year          = {2016},
      volume        = {9},
      number        = {10},
      pages         = {3803--3815},
      doi           = {10.5194/gmd-9-3803-2016},
      archiveprefix = {arXiv},
      eprint        = {1604.05937},
      primaryclass  = {cs.MS}
    }
    
  5. Firedrake: automating the finite element method by composing abstractions
    Florian Rathgeber, David A. Ham, Lawrence Mitchell, Michael Lange, Fabio Luporini, Andrew T. T. McRae, Gheorghe-Teodor Bercea, Graham R. Markall, and Paul H. J. Kelly
    ACM Transactions on Mathematical Software
    doi arxiv:1501.01809
    @article{Rathgeber:2016,
      author        = {Florian Rathgeber and David A. Ham and Lawrence Mitchell and Michael Lange and Fabio Luporini and Andrew T. T. McRae and Gheorghe-Teodor Bercea and Graham R. Markall and Paul H. J. Kelly},
      title         = {{Firedrake: automating the finite element method by composing abstractions}},
      journal       = {ACM Transactions on Mathematical Software},
      year          = {2016},
      volume        = {43},
      number        = {3},
      pages         = {24:1--24:27},
      doi           = {10.1145/2998441},
      archiveprefix = {arXiv},
      eprint        = {1501.01809},
      primaryclass  = {cs.MS}
    }
    
  6. Efficient Modelling and Accurate Certification of Curved Aerospace Laminates
    Fletcher, Tim, Reinarz, Anne, Dodwell, Tim, Butler, Richard, Scheichl, Robert, and Newley, Richard
    in 17th European Conference on Composite Materials
    @inproceedings{Fletcher2016,
      author    = {Fletcher, Tim and  Reinarz, Anne and  Dodwell, Tim and  Butler, Richard and  Scheichl, Robert and  Newley, Richard},
      title     = {{Efficient Modelling and Accurate Certification of Curved Aerospace Laminates}},
      booktitle = {17th European Conference on Composite Materials},
      year      = {2016}
    }
    
  7. Application of high-speed level set segmentation to light sheet fluorescence microscopy
    Carl J. Nelson, Chris G. Willcocks, Philip T.G. Jackson, Philippe Laissue, and Boguslaw Obara
    in Light Sheet Fluorescence Microscopy International
    @inproceedings{nelson2016application,
      author    = {Carl J. Nelson and Chris G. Willcocks and Philip T.G. Jackson and Philippe Laissue and Boguslaw Obara},
      title     = {{Application of high-speed level set segmentation to light sheet fluorescence microscopy}},
      booktitle = {Light Sheet Fluorescence Microscopy International},
      year      = {2016},
      address   = {Sheffield, UK},
      keywords  = {Conference},
      month     = {8}
    }
    
  8. Automated generation and symbolic manipulation of tensor product finite elements
    Andrew T. T. McRae, Gheorghe-Teodor Bercea, Lawrence Mitchell, David A. Ham, and Colin J. Cotter
    SIAM Journal on Scientific Computing
    doi arxiv:1411.2940
    @article{McRae:2016,
      author        = {Andrew T. T. McRae and Gheorghe-Teodor Bercea and Lawrence Mitchell and David A. Ham and Colin J. Cotter},
      title         = {{Automated generation and symbolic manipulation of tensor product finite elements}},
      journal       = {SIAM Journal on Scientific Computing},
      year          = {2016},
      volume        = {38},
      number        = {5},
      pages         = {S25--S47},
      doi           = {10.1137/15M1021167},
      archiveprefix = {arXiv},
      eprint        = {1411.2940},
      primaryclass  = {math.NA}
    }
    
2015
  1. Developing a scalable hybrid MPI/OpenMP unstructured finite element model
    Xiaohu Guo, Michael Lange, Gerard Gorman, Lawrence Mitchell, and Michèle Weiland
    Computers & Fluids
    doi
    @article{Guo:2015,
      author    = {Xiaohu Guo and Michael Lange and Gerard Gorman and Lawrence Mitchell and Michèle Weiland},
      title     = {{Developing a scalable hybrid MPI/OpenMP unstructured finite element model}},
      journal   = {Computers & Fluids},
      year      = {2015},
      volume    = {110},
      pages     = {227--234},
      doi       = {10.1016/j.compfluid.2014.09.007}
    }