DPM: A deep learning PDE augmentation method (with application to large-eddy simulation)

20 November 2019

Papers citing "DPM: A deep learning PDE augmentation method (with application to large-eddy simulation)"

33 / 33 papers shown

Title
LaPON: A Lagrange's-mean-value-theorem-inspired operator network for solving PDEs and its application on NSE Siwen Zhang Xizeng Zhao Zhengzhi Deng Zhaoyuan Huang Gang Tao Nuo Xu Zhouteng Ye 14 0 0 18 May 2025
Multi-level datasets training method in Physics-Informed Neural Networks Yao-Hsuan Tsai Hsiao-Tung Juan Pao-Hsiung Chiu Chao-An Lin AI4CE 39 0 0 30 Apr 2025
Rational-WENO: A lightweight, physically-consistent three-point weighted essentially non-oscillatory scheme S. Shahane Sheide Chammas Deniz A. Bezgin Aaron B. Buhendwa Steffen J. Schmidt ... Spencer H. Bryngelson Yi-Fan Chen Qing Wang Fei Sha Leonardo Zepeda-Núñez 33 1 0 13 Sep 2024
Beyond Closure Models: Learning Chaotic-Systems via Physics-Informed Neural Operators Chuwei Wang Julius Berner Zongyi Li Di Zhou Jiayun Wang Jane Bae Anima Anandkumar AI4CE 36 1 0 09 Aug 2024
A TVD neural network closure and application to turbulent combustion Seung Won Suh J. MacArt Luke N Olson Jonathan B Freund PINN 36 0 0 06 Aug 2024
Learning-based Multi-continuum Model for Multiscale Flow Problems Fan Wang Yating Wang Wing Tat Leung Zongben Xu AI4CE 27 0 0 21 Mar 2024
Data-Efficient Operator Learning via Unsupervised Pretraining and In-Context Learning Wuyang Chen Jialin Song Pu Ren Shashank Subramanian Dmitriy Morozov Michael W. Mahoney AI4CE 54 12 0 24 Feb 2024
JAX-Fluids 2.0: Towards HPC for Differentiable CFD of Compressible Two-phase Flows Deniz A. Bezgin Aaron B. Buhendwa Nikolaus A. Adams 20 9 0 07 Feb 2024
Gradient-free online learning of subgrid-scale dynamics with neural emulators Hugo Frezat Ronan Fablet G. Balarac Julien Le Sommer 27 4 0 30 Oct 2023
A Spectral Approach for Learning Spatiotemporal Neural Differential Equations Mingtao Xia Xiangting Li Qijing Shen Tom Chou 19 0 0 28 Sep 2023
Benchmarking Autoregressive Conditional Diffusion Models for Turbulent Flow Simulation Georg Kohl Li-Wei Chen Nils Thuerey AI4CE DiffM 47 22 0 04 Sep 2023
Differentiable Turbulence: Closure as a partial differential equation constrained optimization Varun Shankar Dibyajyoti Chakraborty V. Viswanathan R. Maulik AI4CE 29 1 0 07 Jul 2023
Dynamic Deep Learning LES Closures: Online Optimization With Embedded DNS Justin A. Sirignano J. MacArt AI4CE 40 7 0 04 Mar 2023
Generalized Neural Closure Models with Interpretability Abhinava Gupta Pierre FJ Lermusiaux AI4CE 32 9 0 15 Jan 2023
Exploring Physical Latent Spaces for High-Resolution Flow Restoration Chloé Paliard Nils Thuerey Kiwon Um AI4CE 25 0 0 21 Nov 2022
Comparison of neural closure models for discretised PDEs Hugo Melchers D. Crommelin B. Koren Vlado Menkovski B. Sanderse 30 15 0 26 Oct 2022
Probabilistic partition of unity networks for high-dimensional regression problems Tiffany Fan N. Trask M. DÉlia Eric F. Darve 19 1 0 06 Oct 2022
Deep Learning Closure Models for Large-Eddy Simulation of Flows around Bluff Bodies Justin A. Sirignano J. MacArt AI4CE PINN 40 19 0 06 Aug 2022
Multiscale Neural Operator: Learning Fast and Grid-independent PDE Solvers Björn Lütjens Catherine H. Crawford C. Watson C. Hill Dava Newman AI4CE 19 9 0 23 Jul 2022
Data-driven Control of Agent-based Models: an Equation/Variable-free Machine Learning Approach Dimitrios G. Patsatzis Lucia Russo Ioannis G. Kevrekidis Constantinos Siettos 26 15 0 12 Jul 2022
AutoKE: An automatic knowledge embedding framework for scientific machine learning Mengge Du Yuntian Chen Dongxiao Zhang AI4CE 41 11 0 11 May 2022
A posteriori learning for quasi-geostrophic turbulence parametrization Hugo Frezat Julien Le Sommer Ronan Fablet G. Balarac Redouane Lguensat 27 56 0 08 Apr 2022
JAX-FLUIDS: A fully-differentiable high-order computational fluid dynamics solver for compressible two-phase flows Deniz A. Bezgin Aaron B. Buhendwa Nikolaus A. Adams AI4CE 15 67 0 25 Mar 2022
Learned Turbulence Modelling with Differentiable Fluid Solvers: Physics-based Loss-functions and Optimisation Horizons Bjorn List Li-Wei Chen Nils Thuerey 34 55 0 14 Feb 2022
Learned Coarse Models for Efficient Turbulence Simulation Kimberly L. Stachenfeld D. Fielding Dmitrii Kochkov M. Cranmer Tobias Pfaff Jonathan Godwin Can Cui S. Ho Peter W. Battaglia Alvaro Sanchez-Gonzalez AI4CE 35 78 0 31 Dec 2021
SPDCinv: Inverse Quantum-Optical Design of High-Dimensional Qudits Eyal Rozenberg Aviv Karnieli O. Yesharim Joshua Foley-Comer Sivan Trajtenberg‐Mills Daniel Freedman A. Bronstein A. Arie 43 0 0 11 Dec 2021
Learning Transport Processes with Machine Intelligence F. Miniati G. Gregori AI4CE 19 3 0 27 Sep 2021
PDE-constrained Models with Neural Network Terms: Optimization and Global Convergence Justin A. Sirignano J. MacArt K. Spiliopoulos PINN AI4CE 29 26 0 18 May 2021
Embedded training of neural-network sub-grid-scale turbulence models J. MacArt Justin A. Sirignano Jonathan B Freund 51 45 0 03 May 2021
Machine learning accelerated computational fluid dynamics Dmitrii Kochkov Jamie A. Smith Ayya Alieva Qing Wang M. Brenner Stephan Hoyer AI4CE 54 829 0 28 Jan 2021
A Deep Learning Approach for Predicting Spatiotemporal Dynamics From Sparsely Observed Data Priyabrata Saha Saibal Mukhopadhyay AI4CE 26 4 0 30 Nov 2020
Learning continuous-time PDEs from sparse data with graph neural networks V. Iakovlev Markus Heinonen Harri Lähdesmäki AI4CE 24 68 0 16 Jun 2020
Automating Turbulence Modeling by Multi-Agent Reinforcement Learning G. Novati Hugues Lascombes de Laroussilhe Petros Koumoutsakos AI4CE 34 15 0 18 May 2020