A composable machine-learning approach for steady-state simulations on
high-resolution grids

A composable machine-learning approach for steady-state simulations on high-resolution grids

11 October 2022

Rishikesh Ranade

Papers citing "A composable machine-learning approach for steady-state simulations on high-resolution grids"

11 / 11 papers shown

Title
Sampling-based Distributed Training with Message Passing Neural Network P. Kakka Sheel Nidhan Rishikesh Ranade Jay Pathak J. MacArt GNN 83 3 0 20 Feb 2025
A domain decomposition-based autoregressive deep learning model for unsteady and nonlinear partial differential equations Sheel Nidhan Haoliang Jiang Lalit Ghule C. Umphrey Rishikesh Ranade Jay Pathak AI4CE 42 0 0 26 Aug 2024
Aero-Nef: Neural Fields for Rapid Aircraft Aerodynamics Simulations Giovanni Catalani Siddhant Agarwal Xavier Bertrand Frédéric Tost Michaël Bauerheim Joseph Morlier AI4CE 49 4 0 29 Jul 2024
Weak baselines and reporting biases lead to overoptimism in machine learning for fluid-related partial differential equations N. McGreivy Ammar Hakim AI4CE 34 43 0 09 Jul 2024
Diffusion model based data generation for partial differential equations Rucha Apte Sheel Nidhan Rishikesh Ranade Jay Pathak DiffM 52 6 0 19 Jun 2023
NLP Inspired Training Mechanics For Modeling Transient Dynamics Lalit Ghule Rishikesh Ranade Jay Pathak AI4CE 13 2 0 04 Nov 2022
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
Parallel Physics-Informed Neural Networks via Domain Decomposition K. Shukla Ameya Dilip Jagtap George Karniadakis PINN 101 274 0 20 Apr 2021
$NVIDIA SimNet^{TM}: an AI-accelerated multi-physics simulation framework$ NVIDIA SimNet^{TM}: an AI-accelerated multi-physics simulation framework O. Hennigh S. Narasimhan M. A. Nabian Akshay Subramaniam Kaustubh Tangsali M. Rietmann J. Ferrandis Wonmin Byeon Z. Fang S. Choudhry PINN AI4CE 93 126 0 14 Dec 2020
Fourier Neural Operator for Parametric Partial Differential Equations Zong-Yi Li Nikola B. Kovachki Kamyar Azizzadenesheli Burigede Liu K. Bhattacharya Andrew M. Stuart Anima Anandkumar AI4CE 235 2,287 0 18 Oct 2020
hp-VPINNs: Variational Physics-Informed Neural Networks With Domain Decomposition E. Kharazmi Zhongqiang Zhang George Karniadakis 128 508 0 11 Mar 2020