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ORCIDMatthew D. Piggott
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2020 – today
- 2024
[c7]Kun Wang, Matthew D. Piggott, Yanghua Wang, Rossella Arcucci:
Neural Network as Transformation Function in Data Assimilation. ICCS (5) 2024: 322-329- [i20]Mingrui Zhang, Chunyang Wang, Stephan Kramer, Joseph G. Wallwork, Siyi Li, Jiancheng Liu, Xiang Chen, Matthew D. Piggott:
Towards Universal Mesh Movement Networks. CoRR abs/2407.00382 (2024) - 2023
- [i19]Mariana C. A. Clare, Simon C. Warder, Robert Neal, B. Bhaskaran, Matthew D. Piggott:
An unsupervised learning approach for predicting wind farm power and downstream wakes using weather patterns. CoRR abs/2302.05886 (2023) - [i18]Sokratis Anagnostopoulos, Jens Bauer, Mariana C. A. Clare, Matthew D. Piggott:
Accelerated wind farm yaw and layout optimisation with multi-fidelity deep transfer learning wake models. CoRR abs/2303.16274 (2023) - [i17]Siyi Li, Arnaud Robert, A. Aldo Faisal, Matthew D. Piggott:
Learning to Optimise Wind Farms with Graph Transformers. CoRR abs/2311.12750 (2023) - 2022
- [j11]Joseph G. Wallwork
, Nicolas Barral, David A. Ham, Matthew D. Piggott:
Goal-Oriented Error Estimation and Mesh Adaptation for Tracer Transport Modelling. Comput. Aided Des. 145: 103187 (2022) - [j10]Mariana C. A. Clare, Stephan C. Kramer, Colin J. Cotter, Matthew D. Piggott:
Calibration, inversion and sensitivity analysis for hydro-morphodynamic models through the application of adjoint methods. Comput. Geosci. 163: 105104 (2022) - [j9]Alexander Kier Christensen, Matthew D. Piggott, Erik van Sebille, Maarten van Reeuwijk, Samraat Pawar:
Investigating microscale patchiness of motile microbes under turbulence in a simulated convective mixed layer. PLoS Comput. Biol. 18(7) (2022) - [c6]Mingrui Zhang, Jianhong Wang, James B. Tlhomole, Matthew D. Piggott:
Learning to Estimate and Refine Fluid Motion with Physical Dynamics. ICML 2022: 26575-26590 - [c5]Wenbin Song, Mingrui Zhang, Joseph G. Wallwork, Junpeng Gao, Zheng Tian, Fanglei Sun, Matthew D. Piggott, Junqing Chen, Zuoqiang Shi, Xiang Chen, Jun Wang:
M2N: Mesh Movement Networks for PDE Solvers. NeurIPS 2022 - [i16]Joseph G. Wallwork, Matthew G. Knepley, Nicolas Barral, Matthew D. Piggott:
Parallel Metric-Based Mesh Adaptation in PETSc using ParMmg. CoRR abs/2201.02806 (2022) - [i15]Wenbin Song, Mingrui Zhang, Joseph G. Wallwork, Junpeng Gao, Zheng Tian, Fanglei Sun, Matthew D. Piggott, Junqing Chen, Zuoqiang Shi, Xiang Chen, Jun Wang:
M2N: Mesh Movement Networks for PDE Solvers. CoRR abs/2204.11188 (2022) - [i14]Mariana C. A. Clare, Matthew D. Piggott:
Bayesian neural networks for the probabilistic forecasting of wind direction and speed using ocean data. CoRR abs/2206.08953 (2022) - [i13]Mingrui Zhang, Jianhong Wang, James Tlhomole, Matthew D. Piggott:
Learning to Estimate and Refine Fluid Motion with Physical Dynamics. CoRR abs/2206.10480 (2022) - [i12]Joseph G. Wallwork, Jingyi Lu, Mingrui Zhang, Matthew D. Piggott:
E2N: Error Estimation Networks for Goal-Oriented Mesh Adaptation. CoRR abs/2207.11233 (2022) - [i11]Siyi Li, Mingrui Zhang, Matthew D. Piggott:
End-to-end Wind Turbine Wake Modelling with Deep Graph Representation Learning. CoRR abs/2211.13649 (2022) - 2021
- [j8]Mariana C. A. Clare, James R. Percival, Athanasios Angeloudis, Colin J. Cotter, Matthew D. Piggott:
Hydro-morphodynamics 2D modelling using a discontinuous Galerkin discretisation. Comput. Geosci. 146: 104658 (2021) - 2020
- [c4]Mingrui Zhang, Matthew D. Piggott:
Unsupervised Learning of Particle Image Velocimetry. ISC Workshops 2020: 102-115 - [i10]Mingrui Zhang, Matthew D. Piggott:
Unsupervised Learning of Particle Image Velocimetry. CoRR abs/2007.14487 (2020)
2010 – 2019
- 2018
- [j7]J. M. Nunez Rattia, James R. Percival, S. J. Neethling, M. D. Piggott:
Modelling local scour near structures with combined mesh movement and mesh optimisation. J. Comput. Phys. 375: 1220-1237 (2018) - 2016
- [j6]Alexandros Adam, Andrew G. Buchan, Matthew D. Piggott, Christopher C. Pain, Jon Hill, Mark A. Goffin:
Adaptive Haar wavelets for the angular discretisation of spectral wave models. J. Comput. Phys. 305: 521-538 (2016) - [i9]Christian T. Jacobs, Matthew D. Piggott, Stephan C. Kramer, Simon W. Funke:
On the validity of tidal turbine array configurations obtained from steady-state adjoint optimisation. CoRR abs/1601.08091 (2016) - [i8]Nicolas Barral, Matthew G. Knepley, Michael Lange, Matthew D. Piggott, Gerard J. Gorman:
Anisotropic mesh adaptation in Firedrake with PETSc DMPlex. CoRR abs/1610.09874 (2016) - 2015
- [c3]Christian T. Jacobs, Alexandros Avdis, Simon L. Mouradian, Matthew D. Piggott:
Integrating Research Data Management into Geographical Information Systems. SDA@TPDL 2015: 7-17 - [i7]Stephan C. Kramer, Matthew D. Piggott:
A correction to the enhanced bottom drag parameterisation of tidal turbines. CoRR abs/1506.03611 (2015) - [i6]Simon W. Funke, Stephan C. Kramer, Matthew D. Piggott:
Design optimisation and resource assessment for tidal-stream renewable energy farms using a new continuous turbine approach. CoRR abs/1507.05795 (2015) - [i5]Christian T. Jacobs, Alexandros Avdis, Simon L. Mouradian, Matthew D. Piggott:
Integrating Research Data Management into Geographical Information Systems. CoRR abs/1509.04729 (2015) - [i4]Alexandros Avdis, Christian T. Jacobs, Jon Hill, Matthew D. Piggott, Gerard J. Gorman:
Shoreline and Bathymetry Approximation in Mesh Generation for Tidal Renewable Simulations. CoRR abs/1510.01560 (2015) - 2014
- [i3]Christian T. Jacobs, Alexandros Avdis, Gerard J. Gorman, Matthew D. Piggott:
PyRDM: A Python-based library for automating the management and online publication of scientific software and data. CoRR abs/1405.7290 (2014) - [i2]George L. Barnett, Simon W. Funke, Matthew D. Piggott:
Hybrid global-local optimisation algorithms for the layout design of tidal turbine arrays. CoRR abs/1410.2476 (2014) - 2013
- [i1]Simon W. Funke, Patrick E. Farrell, M. D. Piggott:
Tidal turbine array optimisation using the adjoint approach. CoRR abs/1304.1768 (2013) - 2012
- [j5]James Southern, Gerard J. Gorman, M. D. Piggott, Patrick E. Farrell:
Parallel anisotropic mesh adaptivity with dynamic load balancing for cardiac electrophysiology. J. Comput. Sci. 3(1-2): 8-16 (2012) - [c2]Gerard J. Gorman, James Southern, Patrick E. Farrell, M. D. Piggott, Georgios Rokos, Paul H. J. Kelly:
Hybrid OpenMP/MPI Anisotropic Mesh Smoothing. ICCS 2012: 1513-1522 - 2010
- [j4]James Southern, Gerard J. Gorman, M. D. Piggott, Patrick E. Farrell, Miguel O. Bernabeu, Joe Pitt-Francis:
Simulating cardiac electrophysiology using anisotropic mesh adaptivity. J. Comput. Sci. 1(2): 82-88 (2010) - [c1]James Southern, Gerard J. Gorman, M. D. Piggott, Patrick E. Farrell, Miguel O. Bernabeu, Joe Pitt-Francis:
Anisotropic mesh adaptivity for cardiac electrophysiology. ICCS 2010: 935-944
2000 – 2009
- 2008
- [j3]Gerard J. Gorman, M. D. Piggott, M. R. Wells, Christopher C. Pain, Peter A. Allison:
A systematic approach to unstructured mesh generation for ocean modelling using GMT and Terreno. Comput. Geosci. 34(12): 1721-1731 (2008) - 2007
- [j2]Gerard J. Gorman, M. D. Piggott, Christopher C. Pain:
Shoreline approximation for unstructured mesh generation. Comput. Geosci. 33(5): 666-677 (2007) - 2006
- [j1]P. W. Power, Christopher C. Pain, M. D. Piggott, Fangxin Fang, Gerard J. Gorman, A. P. Umpleby, Anthony J. H. Goddard, I. M. Navon:
Adjoint A Posteriori Error Measures for Anisotropic Mesh Optimisation. Comput. Math. Appl. 52(8-9): 1213-1242 (2006)
Coauthor Index
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