Feasibility Study on Active Learning of Smart Surrogates for Scientific
Simulations

Feasibility Study on Active Learning of Smart Surrogates for Scientific Simulations

10 July 2024

Pradeep Bajracharya

J. Q. Toledo-Marín

Geoffrey C. Fox

Linwei Wang

Papers citing "Feasibility Study on Active Learning of Smart Surrogates for Scientific Simulations"

6 / 6 papers shown

Title
Active Learning for Neural PDE Solvers Daniel Musekamp Marimuthu Kalimuthu David Holzmüller Makoto Takamoto Carlos Fernandez AI4CE 41 4 0 02 Aug 2024
Towards Multi-spatiotemporal-scale Generalized PDE Modeling Jayesh K. Gupta Johannes Brandstetter AI4CE 53 117 0 30 Sep 2022
Deep Active Learning by Leveraging Training Dynamics Haonan Wang Wei Huang Ziwei Wu A. Margenot Hanghang Tong Jingrui He AI4CE 17 31 0 16 Oct 2021
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 197 2,254 0 18 Oct 2020
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 245 9,042 0 06 Jun 2015
U-Net: Convolutional Networks for Biomedical Image Segmentation Olaf Ronneberger Philipp Fischer Thomas Brox SSeg 3DV 226 74,467 0 18 May 2015