Teaching the Incompressible Navier-Stokes Equations to Fast Neural
Surrogate Models in 3D

Teaching the Incompressible Navier-Stokes Equations to Fast Neural Surrogate Models in 3D

22 December 2020

Michael Weinmann

Papers citing "Teaching the Incompressible Navier-Stokes Equations to Fast Neural Surrogate Models in 3D"

18 / 18 papers shown

Title
Metamizer: a versatile neural optimizer for fast and accurate physics simulations Nils Wandel Stefan Schulz Reinhard Klein PINN AI4CE 39 0 0 10 Oct 2024
Improving PINNs By Algebraic Inclusion of Boundary and Initial Conditions Mohan Ren Zhihao Fang Keren Li Anirbit Mukherjee PINN AI4CE 39 0 0 30 Jul 2024
Weak baselines and reporting biases lead to overoptimism in machine learning for fluid-related partial differential equations N. McGreivy Ammar Hakim AI4CE 29 42 0 09 Jul 2024
Pi-fusion: Physics-informed diffusion model for learning fluid dynamics Jing Qiu Jiancheng Huang Xiangdong Zhang Zeng Lin Minglei Pan Zengding Liu F. Miao AI4CE 30 3 0 06 Jun 2024
Automatic Differentiation is Essential in Training Neural Networks for Solving Differential Equations Chuqi Chen Yahong Yang Yang Xiang Wenrui Hao 26 2 0 23 May 2024
A conditional latent autoregressive recurrent model for generation and forecasting of beam dynamics in particle accelerators M. Rautela Alan Williams A. Scheinker 39 4 0 19 Mar 2024
Investigating the Ability of PINNs To Solve Burgers' PDE Near Finite-Time BlowUp Dibyakanti Kumar Anirbit Mukherjee 31 2 0 08 Oct 2023
Geometry-Informed Neural Operator for Large-Scale 3D PDEs Zong-Yi Li Nikola B. Kovachki Chris Choy Boyi Li Jean Kossaifi ... M. A. Nabian Maximilian Stadler Christian Hundt Kamyar Azizzadenesheli Anima Anandkumar AI4CE 23 127 0 01 Sep 2023
Auxiliary-Tasks Learning for Physics-Informed Neural Network-Based Partial Differential Equations Solving Junjun Yan Xinhai Chen Zhichao Wang Enqiang Zhou Jie Liu PINN AI4CE 24 1 0 12 Jul 2023
ST-PINN: A Self-Training Physics-Informed Neural Network for Partial Differential Equations Junjun Yan Xinhai Chen Zhichao Wang Enqiang Zhoui Jie Liu PINN DiffM AI4CE 19 10 0 15 Jun 2023
Monte Carlo Neural PDE Solver for Learning PDEs via Probabilistic Representation Rui Zhang Qi Meng Rongchan Zhu Yue Wang Wenlei Shi Shihua Zhang Zhi-Ming Ma Tie-Yan Liu DiffM AI4CE 44 4 0 10 Feb 2023
LSA-PINN: Linear Boundary Connectivity Loss for Solving PDEs on Complex Geometry Jian Cheng Wong P. Chiu C. Ooi M. Dao Yew-Soon Ong AI4CE PINN 22 10 0 03 Feb 2023
LordNet: An Efficient Neural Network for Learning to Solve Parametric Partial Differential Equations without Simulated Data Xinquan Huang Wenlei Shi Xiaotian Gao Xinran Wei Jia Zhang Jiang Bian Mao Yang Tie-Yan Liu PINN 25 10 0 19 Jun 2022
Accelerating hydrodynamic simulations of urban drainage systems with physics-guided machine learning Rocco Palmitessa M. Grum A. Engsig-Karup Roland Löwe AI4CE 19 20 0 24 May 2022
Towards Size-Independent Generalization Bounds for Deep Operator Nets Pulkit Gopalani Sayar Karmakar Dibyakanti Kumar Anirbit Mukherjee AI4CE 21 5 0 23 May 2022
Multi-resolution partial differential equations preserved learning framework for spatiotemporal dynamics Xin-Yang Liu Min Zhu Lu Lu Hao Sun Jian-Xun Wang PINN AI4CE 22 45 0 09 May 2022
CAN-PINN: A Fast Physics-Informed Neural Network Based on Coupled-Automatic-Numerical Differentiation Method P. Chiu Jian Cheng Wong C. Ooi M. Dao Yew-Soon Ong PINN 17 204 0 29 Oct 2021
SPNets: Differentiable Fluid Dynamics for Deep Neural Networks Connor Schenck D. Fox PINN 3DPC AI4CE 167 161 0 15 Jun 2018