Hidden Fluid Mechanics: A Navier-Stokes Informed Deep Learning Framework for Assimilating Flow Visualization Data

13 August 2018

Papers citing "Hidden Fluid Mechanics: A Navier-Stokes Informed Deep Learning Framework for Assimilating Flow Visualization Data"

32 / 32 papers shown

Title
Data-driven Modeling of Combined Sewer Systems for Urban Sustainability: An Empirical Evaluation Vipin Singh Tianheng Ling Teodor Chiaburu Felix Biessmann AI4CE 41 1 0 21 Aug 2024
Physics-informed Deep Learning to Solve Three-dimensional Terzaghi Consolidation Equation: Forward and Inverse Problems Biao Yuan Ana Heitor He Wang Xiaohui Chen AI4CE PINN 34 1 0 08 Jan 2024
Improving deep learning precipitation nowcasting by using prior knowledge M. Choma Petr Simánek Jakub Bartel 34 0 0 27 Jan 2023
Physics-informed Neural Networks with Periodic Activation Functions for Solute Transport in Heterogeneous Porous Media Salah A. Faroughi Ramin Soltanmohammad Pingki Datta S. K. Mahjour S. Faroughi 21 22 0 17 Dec 2022
Physics-Guided, Physics-Informed, and Physics-Encoded Neural Networks in Scientific Computing Salah A. Faroughi N. Pawar C. Fernandes Maziar Raissi Subasish Das N. Kalantari S. K. Mahjour PINN AI4CE 27 49 0 14 Nov 2022
A comparison of PINN approaches for drift-diffusion equations on metric graphs J. Blechschmidt Jan-Frederik Pietschman Tom-Christian Riemer Martin Stoll M. Winkler 18 2 0 15 May 2022
Leveraging Stochastic Predictions of Bayesian Neural Networks for Fluid Simulations Maximilian Mueller Robin Greif Frank Jenko Nils Thuerey 24 3 0 02 May 2022
Physics-constrained Unsupervised Learning of Partial Differential Equations using Meshes M. Michelis Robert K. Katzschmann AI4CE 27 1 0 30 Mar 2022
Error estimates for physics informed neural networks approximating the Navier-Stokes equations Tim De Ryck Ameya Dilip Jagtap S. Mishra PINN 49 115 0 17 Mar 2022
HyperPINN: Learning parameterized differential equations with physics-informed hypernetworks Filipe de Avila Belbute-Peres Yi-fan Chen Fei Sha PINN 16 38 0 28 Oct 2021
Spline-PINN: Approaching PDEs without Data using Fast, Physics-Informed Hermite-Spline CNNs Nils Wandel Michael Weinmann Michael Neidlin Reinhard Klein AI4CE 58 60 0 15 Sep 2021
IDRLnet: A Physics-Informed Neural Network Library Wei Peng Jun Zhang Weien Zhou Xiaoyu Zhao W. Yao Xiaoqian Chen PINN AI4CE 33 15 0 09 Jul 2021
Error analysis for physics informed neural networks (PINNs) approximating Kolmogorov PDEs Tim De Ryck Siddhartha Mishra PINN 21 100 0 28 Jun 2021
Efficient training of physics-informed neural networks via importance sampling M. A. Nabian R. J. Gladstone Hadi Meidani DiffM PINN 71 222 0 26 Apr 2021
Transferable Model for Shape Optimization subject to Physical Constraints Lukas Harsch Johannes Burgbacher S. Riedelbauch AI4CE 24 1 0 19 Mar 2021
Teaching the Incompressible Navier-Stokes Equations to Fast Neural Surrogate Models in 3D Nils Wandel Michael Weinmann Reinhard Klein AI4CE 26 50 0 22 Dec 2020
Bridging the Gap: Machine Learning to Resolve Improperly Modeled Dynamics Maan Qraitem D. Kularatne Eric Forgoston M. A. Hsieh AI4CE 23 10 0 23 Aug 2020
Semi Conditional Variational Auto-Encoder for Flow Reconstruction and Uncertainty Quantification from Limited Observations K. Gundersen A. Oleynik N. Blaser G. Alendal BDL 27 27 0 19 Jul 2020
Estimates on the generalization error of Physics Informed Neural Networks (PINNs) for approximating PDEs Siddhartha Mishra Roberto Molinaro PINN 25 171 0 29 Jun 2020
Enhancing accuracy of deep learning algorithms by training with low-discrepancy sequences Siddhartha Mishra T. Konstantin Rusch 19 49 0 26 May 2020
Active Training of Physics-Informed Neural Networks to Aggregate and Interpolate Parametric Solutions to the Navier-Stokes Equations Christopher J. Arthurs A. King PINN 37 51 0 02 May 2020
Physics-Guided Machine Learning for Scientific Discovery: An Application in Simulating Lake Temperature Profiles X. Jia J. Willard Anuj Karpatne J. Read Jacob Aaron Zwart M. Steinbach Vipin Kumar AI4CE PINN 18 207 0 28 Jan 2020
Learning to Control PDEs with Differentiable Physics Philipp Holl V. Koltun Nils Thuerey AI4CE PINN 44 185 0 21 Jan 2020
A Derivative-Free Method for Solving Elliptic Partial Differential Equations with Deep Neural Networks Jihun Han Mihai Nica A. Stinchcombe 22 49 0 17 Jan 2020
Understanding and mitigating gradient pathologies in physics-informed neural networks Sizhuang He Yujun Teng P. Perdikaris AI4CE PINN 23 291 0 13 Jan 2020
Variational Physics-Informed Neural Networks For Solving Partial Differential Equations E. Kharazmi Z. Zhang George Karniadakis 21 236 0 27 Nov 2019
A Multi-level procedure for enhancing accuracy of machine learning algorithms K. Lye Siddhartha Mishra Roberto Molinaro 15 32 0 20 Sep 2019
DeepXDE: A deep learning library for solving differential equations Lu Lu Xuhui Meng Zhiping Mao George Karniadakis PINN AI4CE 25 1,485 0 10 Jul 2019
Deep learning observables in computational fluid dynamics K. Lye Siddhartha Mishra Deep Ray OOD AI4CE 13 158 0 07 Mar 2019
Deep Learning Methods for Reynolds-Averaged Navier-Stokes Simulations of Airfoil Flows Nils Thuerey Konstantin Weissenow L. Prantl Xiangyu Y. Hu AI4CE 25 377 0 18 Oct 2018
Physics-Driven Regularization of Deep Neural Networks for Enhanced Engineering Design and Analysis M. A. Nabian Hadi Meidani PINN AI4CE 21 57 0 11 Oct 2018
General solutions for nonlinear differential equations: a rule-based self-learning approach using deep reinforcement learning Shiyin Wei Xiaowei Jin Hui Li AI4CE 39 39 0 13 May 2018