Title
DiffESM: Conditional Emulation of Temperature and Precipitation in Earth System Models with 3D Diffusion Models Seth Bassetti Brian Hutchinson Claudia Tebaldi Ben Kravitz 87 5 0 17 Sep 2024
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A Fast Learning-Based Surrogate of Electrical Machines using a Reduced Basis Alejandro Ribés Nawfal Benchekroun Théo Delagnes AI4CE 80 1 0 27 Jun 2024
AI-coupled HPC Workflow Applications, Middleware and Performance Wes Brewer Ana Gainaru Frédéric Suter Feiyi Wang M. Emani S. Jha 84 10 0 20 Jun 2024
Diffusion-Based Joint Temperature and Precipitation Emulation of Earth System Models Katie Christensen Lyric Otto Seth Bassetti Claudia Tebaldi Brian Hutchinson 106 0 0 12 Apr 2024
ML4PhySim : Machine Learning for Physical Simulations Challenge (The airfoil design) Mouadh Yagoubi Milad Leyli-Abadi David Danan Jean-Patrick Brunet Jocelyn Ahmed Mazari F. Bonnet A. Farjallah Marc Schoenauer Patrick Gallinari AI4CE 68 3 0 03 Mar 2024
High Throughput Training of Deep Surrogates from Large Ensemble Runs Lucas Meyer M. Schouler R. Caulk Alejandro Ribés Bruno Raffin AI4CE 57 6 0 28 Sep 2023
Reduced Simulations for High-Energy Physics, a Middle Ground for Data-Driven Physics Research Uraz Odyurt S. N. Swatman A. Varbanescu Sascha Caron 39 3 0 30 Aug 2023
Learning and Generalizing Polynomials in Simulation Metamodeling J. Hauch Christoffer Riis Francisco Câmara Pereira 23 0 0 20 Jul 2023
Fourier Neural Operators for Arbitrary Resolution Climate Data Downscaling Qidong Yang Alex Hernandez-Garcia P. Harder Venkatesh Ramesh Prasanna Sattegeri Daniela Szwarcman C. Watson David Rolnick AI4CE 67 24 0 23 May 2023
A Neural Emulator for Uncertainty Estimation of Fire Propagation Andrew Bolt Conrad Sanderson J. Dabrowski C. Huston Petra Kuhnert 65 3 0 10 May 2023
Adapting U-Net for linear elastic stress estimation in polycrystal Zr microstructures J. D. Langcaster D. Balint M. Wenman 38 1 0 15 Mar 2023
Myths and Legends in High-Performance Computing Satoshi Matsuoka Jens Domke Mohamed Wahib Aleksandr Drozd Torsten Hoefler 103 14 0 06 Jan 2023
Exploring Randomly Wired Neural Networks for Climate Model Emulation William Yik Sam J. Silva A. Geiss D. Watson‐Parris 62 3 0 06 Dec 2022
On the Compatibility between Neural Networks and Partial Differential Equations for Physics-informed Learning Kuangdai Leng Jeyan Thiyagalingam PINN 64 3 0 01 Dec 2022
Data-driven Science and Machine Learning Methods in Laser-Plasma Physics Andreas Döpp C. Eberle S. Howard F. Irshad Jinpu Lin M. Streeter AI4CE 83 72 0 30 Nov 2022
Can denoising diffusion probabilistic models generate realistic astrophysical fields? N. Mudur D. Finkbeiner DiffM 63 15 0 22 Nov 2022
Few-shot Generation of Personalized Neural Surrogates for Cardiac Simulation via Bayesian Meta-Learning Xiajun Jiang Zhiyuan Li R. Missel Md Shakil Zaman B. Zenger W. Good Rob S. MacLeod J. Sapp Linwei Wang MedIm 57 2 0 06 Oct 2022
AI-coupled HPC Workflows S. Jha V. Pascuzzi Matteo Turilli 67 10 0 24 Aug 2022
A Spatio-Temporal Neural Network Forecasting Approach for Emulation of Firefront Models Andrew Bolt C. Huston Petra Kuhnert J. Dabrowski J. Hilton Conrad Sanderson AI4TS 123 11 0 17 Jun 2022
A posteriori learning for quasi-geostrophic turbulence parametrization Hugo Frezat Julien Le Sommer Ronan Fablet G. Balarac Redouane Lguensat 67 58 0 08 Apr 2022
An Emulation Framework for Fire Front Spread Andrew Bolt J. Dabrowski C. Huston Petra Kuhnert 10 1 0 23 Mar 2022
Reducing the Long Tail Losses in Scientific Emulations with Active Learning Yi Heng Lim M. F. Kasim 48 0 0 15 Nov 2021
Designing Machine Learning Surrogates using Outputs of Molecular Dynamics Simulations as Soft Labels J. Kadupitiya Nasim Anousheh V. Jadhao AI4CE SyDa 13 0 0 27 Oct 2021
Learning Transport Processes with Machine Intelligence F. Miniati G. Gregori AI4CE 60 4 0 27 Sep 2021
Opportunistic Emulation of Computationally Expensive Simulations via Deep Learning Conrad Sanderson D. Pagendam B. Power Frederick Bennett Ross Darnell 104 2 0 25 Aug 2021
Self-learning Emulators and Eigenvector Continuation Avik Sarkar Dean Lee 61 17 0 28 Jul 2021
Finite Basis Physics-Informed Neural Networks (FBPINNs): a scalable domain decomposition approach for solving differential equations Benjamin Moseley Andrew Markham T. Nissen‐Meyer PINN 91 227 0 16 Jul 2021
Deep physical neural networks enabled by a backpropagation algorithm for arbitrary physical systems Logan G. Wright Tatsuhiro Onodera Martin M. Stein Tianyu Wang Darren T. Schachter Zoey Hu Peter L. McMahon PINN AI4CE 109 502 0 27 Apr 2021
Optimized and autonomous machine learning framework for characterizing pores, particles, grains and grain boundaries in microstructural images Roberto Perera D. Guzzetti V. Agrawal 28 26 0 16 Jan 2021
Towards fast machine-learning-assisted Bayesian posterior inference of microseismic event location and source mechanism Davide Piras A. Mancini Ana M. G. Ferreira B. Joachimi Michael P. Hobson 56 5 0 12 Jan 2021
$ξ$ -torch: differentiable scientific computing library M. F. Kasim S. Vinko AI4CE 38 5 0 05 Oct 2020
Robust posterior inference when statistically emulating forward simulations G. Aslanyan R. Easther Nathan Musoke Layne Price 8 0 0 24 Apr 2020
Integrating Scientific Knowledge with Machine Learning for Engineering and Environmental Systems J. Willard X. Jia Shaoming Xu M. Steinbach Vipin Kumar AI4CE 158 415 0 10 Mar 2020
A framework for deep learning emulation of numerical models with a case study in satellite remote sensing Kate Duffy T. Vandal Weile Wang R. Nemani A. Ganguly 40 8 0 29 Oct 2019