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Multi-Resolution Active Learning of Fourier Neural Operators

Multi-Resolution Active Learning of Fourier Neural Operators

29 September 2023
Shibo Li
Xin Yu
Wei W. Xing
Mike Kirby
Akil Narayan
Shandian Zhe
    AI4CE
ArXivPDFHTML

Papers citing "Multi-Resolution Active Learning of Fourier Neural Operators"

9 / 9 papers shown
Title
Learning Dual-Arm Coordination for Grasping Large Flat Objects
Learning Dual-Arm Coordination for Grasping Large Flat Objects
Yongliang Wang
H. Kasaei
32
0
0
04 Apr 2025
Active Learning for Neural PDE Solvers
Active Learning for Neural PDE Solvers
Daniel Musekamp
Marimuthu Kalimuthu
David Holzmüller
Makoto Takamoto
Carlos Fernandez
AI4CE
41
4
0
02 Aug 2024
Invertible Fourier Neural Operators for Tackling Both Forward and Inverse Problems
Invertible Fourier Neural Operators for Tackling Both Forward and Inverse Problems
Da Long
Zhitong Xu
Qiwei Yuan
Yin Yang
Shandian Zhe
AI4CE
64
5
0
18 Feb 2024
Batch Multi-Fidelity Active Learning with Budget Constraints
Batch Multi-Fidelity Active Learning with Budget Constraints
Shibo Li
J. M. Phillips
Xin Yu
Robert M. Kirby
Shandian Zhe
75
15
0
23 Oct 2022
Infinite-Fidelity Coregionalization for Physical Simulation
Infinite-Fidelity Coregionalization for Physical Simulation
Shibo Li
Z. Wang
Robert M. Kirby
Shandian Zhe
AI4CE
18
6
0
01 Jul 2022
Multiwavelet-based Operator Learning for Differential Equations
Multiwavelet-based Operator Learning for Differential Equations
Gaurav Gupta
Xiongye Xiao
P. Bogdan
124
198
0
28 Sep 2021
Fourier Neural Operator for Parametric Partial Differential Equations
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
203
2,254
0
18 Oct 2020
Simple and Scalable Predictive Uncertainty Estimation using Deep
  Ensembles
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles
Balaji Lakshminarayanan
Alexander Pritzel
Charles Blundell
UQCV
BDL
268
5,635
0
05 Dec 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in
  Deep Learning
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCV
BDL
247
9,042
0
06 Jun 2015
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