$NVIDIA SimNet^{TM}: an AI-accelerated multi-physics simulation framework$

NVIDIA SimNet^{TM}: an AI-accelerated multi-physics simulation framework

14 December 2020

Papers citing "NVIDIA SimNet^{TM}: an AI-accelerated multi-physics simulation framework"

50 / 64 papers shown

Geometric Operator Learning with Optimal Transport

201

26 Jul 2025

Enhanced Vascular Flow Simulations in Aortic Aneurysm via Physics-Informed Neural Networks and Deep Operator Networks

Oscar L. Cruz-González

Valérie Deplano

Badih Ghattas

MedIm AI4CE

246

19 Mar 2025

LatticeGraphNet: A two-scale graph neural operator for simulating lattice structures

222

01 Feb 2024

PirateNets: Physics-informed Deep Learning with Residual Adaptive Networks

632

101

01 Feb 2024

Accurate and Fast Fischer-Tropsch Reaction Microkinetics using PINNs

237

17 Nov 2023

High Throughput Training of Deep Surrogates from Large Ensemble RunsInternational Conference for High Performance Computing, Networking, Storage and Analysis (SC), 2023

251

28 Sep 2023

Deep Learning in Deterministic Computational Mechanics

L. Herrmann

Stefan Kollmannsberger

AI4CE PINN

393

27 Sep 2023

Physics-informed machine learning of the correlation functions in bulk fluidsThe Physics of Fluids (Phys. Fluids), 2023

Wenqian Chen

Peiyuan Gao

P. Stinis

167

02 Sep 2023

Breaking Boundaries: Distributed Domain Decomposition with Scalable Physics-Informed Neural PDE SolversInternational Conference for High Performance Computing, Networking, Storage and Analysis (SC), 2023

Arthur Feeney

Zitong Li

Ramin Bostanabad

Aparna Chandramowlishwaran

AI4CE

242

28 Aug 2023

Bayesian Reasoning for Physics Informed Neural Networks

K. Graczyk

Kornel Witkowski

314

25 Aug 2023

Learning Only On Boundaries: a Physics-Informed Neural operator for Solving Parametric Partial Differential Equations in Complex GeometriesNeural Computation (Neural Comput.), 2023

263

24 Aug 2023

An Expert's Guide to Training Physics-informed Neural Networks

384

172

16 Aug 2023

PINNacle: A Comprehensive Benchmark of Physics-Informed Neural Networks for Solving PDEsNeural Information Processing Systems (NeurIPS), 2023

Hang Su

...

Jun Zhu

353

15 Jun 2023

RANS-PINN based Simulation Surrogates for Predicting Turbulent Flows

Shinjan Ghosh

Amit Chakraborty

Georgia Olympia Brikis

Biswadip Dey

PINN AI4CE

289

09 Jun 2023

An information field theory approach to Bayesian state and parameter estimation in dynamical systemsJournal of Computational Physics (JCP), 2023

Kairui Hao

Ilias Bilionis

259

03 Jun 2023

Implicit Stochastic Gradient Descent for Training Physics-informed Neural NetworksAAAI Conference on Artificial Intelligence (AAAI), 2023

171

03 Mar 2023

DeepOHeat: Operator Learning-based Ultra-fast Thermal Simulation in 3D-IC DesignDesign Automation Conference (DAC), 2023

197

25 Feb 2023

h-analysis and data-parallel physics-informed neural networksScientific Reports (Sci Rep), 2023

Paul Escapil-Inchauspé

G. A. Ruz

PINN AI4CE

349

17 Feb 2023

Can Physics-Informed Neural Networks beat the Finite Element Method?IMA Journal of Applied Mathematics (IMA J. Appl. Math.), 2023

T. G. Grossmann

Urszula Julia Komorowska

J. Latz

Carola-Bibiane Schönlieb

PINN AI4CE

312

185

08 Feb 2023

Temporal Consistency Loss for Physics-Informed Neural NetworksThe Physics of Fluids (Phys. Fluids), 2023

234

30 Jan 2023

Investigations on convergence behaviour of Physics Informed Neural Networks across spectral ranges and derivative ordersIEEE Symposium Series on Computational Intelligence (IEEE SSCI), 2022

161

07 Jan 2023

SciAI4Industry -- Solving PDEs for industry-scale problems with deep learning

310

23 Nov 2022

A Curriculum-Training-Based Strategy for Distributing Collocation Points during Physics-Informed Neural Network Training

Marcus Münzer

C. Bard

233

21 Nov 2022

Physics-Informed Koopman Network

284

17 Nov 2022

Separable PINN: Mitigating the Curse of Dimensionality in Physics-Informed Neural Networks

274

16 Nov 2022

PDEBENCH: An Extensive Benchmark for Scientific Machine LearningNeural Information Processing Systems (NeurIPS), 2022

763

384

13 Oct 2022

A composable machine-learning approach for steady-state simulations on high-resolution gridsNeural Information Processing Systems (NeurIPS), 2022

280

11 Oct 2022

Implicit Neural Spatial Representations for Time-dependent PDEsInternational Conference on Machine Learning (ICML), 2022

550

30 Sep 2022

A Thermal Machine Learning Solver For Chip SimulationWorkshop on Machine Learning for CAD (ML4CAD), 2022

292

10 Sep 2022

NeuralUQ: A comprehensive library for uncertainty quantification in neural differential equations and operators

276

25 Aug 2022

PIXEL: Physics-Informed Cell Representations for Fast and Accurate PDE SolversAAAI Conference on Artificial Intelligence (AAAI), 2022

260

26 Jul 2022

The Deep Ritz Method for Parametric

p

-Dirichlet Problems

A. Kaltenbach

Marius Zeinhofer

140

05 Jul 2022

Fast Neural Network based Solving of Partial Differential Equations

238

18 May 2022

Scalable algorithms for physics-informed neural and graph networksData-Centric Engineering (DE), 2022

390

16 May 2022

RANG: A Residual-based Adaptive Node Generation Method for Physics-Informed Neural Networks

349

02 May 2022

Qade: Solving Differential Equations on Quantum AnnealersQuantum Science and Technology (QST), 2022

J. C. Criado

M. Spannowsky

334

07 Apr 2022

Physics Informed RNN-DCT Networks for Time-Dependent Partial Differential EquationsInternational Conference on Conceptual Structures (ICCS), 2022

211

24 Feb 2022

Physics-informed neural networks for solving parametric magnetostatic problemsIEEE transactions on energy conversion (IEEE Trans. Energy Convers.), 2022

Andrés Beltrán-Pulido

Ilias Bilionis

D. Aliprantis

258

08 Feb 2022

Physics-informed neural networks for non-Newtonian fluid thermo-mechanical problems: an application to rubber calendering processEngineering applications of artificial intelligence (EAAI), 2022

Thi Nguyen Khoa Nguyen

372

31 Jan 2022

Scientific Machine Learning through Physics-Informed Neural Networks: Where we are and What's nextJournal of Scientific Computing (J. Sci. Comput.), 2022

S. Cuomo

Vincenzo Schiano Di Cola

661

2,104

14 Jan 2022

PINNs for the Solution of the Hyperbolic Buckley-Leverett Problem with a Non-convex Flux Function

W. Diab

M. A. Kobaisi

PINN

191

29 Dec 2021

Solving Partial Differential Equations with Point Source Based on Physics-Informed Neural Networks

...

225

02 Nov 2021

CAN-PINN: A Fast Physics-Informed Neural Network Based on Coupled-Automatic-Numerical Differentiation MethodComputer Methods in Applied Mechanics and Engineering (CMAME), 2021

394

331

29 Oct 2021

One-Shot Transfer Learning of Physics-Informed Neural Networks

390

21 Oct 2021

A composable autoencoder-based iterative algorithm for accelerating numerical simulations

303

07 Oct 2021

Learning in Sinusoidal Spaces with Physics-Informed Neural Networks

Abhishek Gupta

218

112

20 Sep 2021

Characterizing possible failure modes in physics-informed neural networks

Aditi S. Krishnapriyan

503

1,014

02 Sep 2021

Unsupervised Reservoir Computing for Solving Ordinary Differential Equations

M. Mattheakis

H. Joy

P. Protopapas

258

25 Aug 2021

Training multi-objective/multi-task collocation physics-informed neural network with student/teachers transfer learnings

B. Bahmani

WaiChing Sun

PINN AI4CE

286

24 Jul 2021

Finite Basis Physics-Informed Neural Networks (FBPINNs): a scalable domain decomposition approach for solving differential equationsAdvances in Computational Mathematics (Adv. Comput. Math.), 2021

251

359

16 Jul 2021