PLAIDbenchmarks

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AI & ML interests

AI and ML for physics

authored a paper 10 months ago

Physics-Learning AI Datamodel (PLAID) datasets: a collection of physics simulations for machine learning

Paper • 2505.02974 • Published May 5, 2025

authored a paper 11 months ago

O-MMGP: Optimal Mesh Morphing Gaussian Process Regression for Solving PDEs with non-Parametric Geometric Variations

Paper • 2502.11632 • Published Feb 17, 2025

authored a paper about 1 year ago

Learning large scale industrial physics simulations

Paper • 2502.08295 • Published Feb 12, 2025

authored 17 papers over 1 year ago

An elasticity-based mesh morphing technique with application to reduced-order modeling

Paper • 2407.02433 • Published Jul 2, 2024

A Nonintrusive Distributed Reduced Order Modeling Framework for nonlinear structural mechanics -- application to elastoviscoplastic computations

Paper • 1812.07228 • Published Dec 18, 2018

An error indicator-based adaptive reduced order model for nonlinear structural mechanics -- application to high-pressure turbine blades

Paper • 1904.09123 • Published Apr 19, 2019

Nonintrusive approximation of parametrized limits of matrix power algorithms -- application to matrix inverses and log-determinants

Paper • 1710.02488 • Published Oct 6, 2017

Variants of the Empirical Interpolation Method: symmetric formulation, choice of norms and rectangular extension

Paper • 1508.05330 • Published Aug 21, 2015

A Fast Summation Method for translation invariant kernels

Paper • 1408.0210 • Published Aug 1, 2014

Boundary Element and Finite Element Coupling for Aeroacoustics Simulations

Paper • 1402.2439 • Published Feb 11, 2014

A nonintrusive Reduced Basis Method applied to aeroacoustic simulations

Paper • 1401.3684 • Published Jan 15, 2014

Accurate and efficient evaluation of the a posteriori error estimator in the reduced basis method

Paper • 1212.0970 • Published Dec 5, 2012

Coupled BEM-FEM for the convected Helmholtz equation with non-uniform flow in a bounded domain

Paper • 1303.6923 • Published Mar 27, 2013

A nonintrusive method to approximate linear systems with nonlinear parameter dependence

Paper • 1307.4330 • Published Jul 16, 2013

Accurate a posteriori error evaluation in the reduced basis method

Paper • 1205.6051 • Published May 28, 2012

A priori compression of convolutional neural networks for wave simulators

Paper • 2304.04964 • Published Apr 11, 2023

Uncertainty quantification in a mechanical submodel driven by a Wasserstein-GAN

Paper • 2110.13680 • Published Oct 26, 2021

Optimal piecewise linear data compression for solutions of parametrized partial differential equations

Paper • 2108.12291 • Published Aug 27, 2021

Uncertainty quantification for industrial design using dictionaries of reduced order models

Paper • 2108.04012 • Published Aug 9, 2021

Data augmentation and feature selection for automatic model recommendation in computational physics

Paper • 2101.04530 • Published Jan 12, 2021