Linearization Turns Neural Operators into Function-Valued Gaussian Processes

7 June 2024

Papers citing "Linearization Turns Neural Operators into Function-Valued Gaussian Processes"

6 / 6 papers shown

Title
Position: Bayesian Deep Learning is Needed in the Age of Large-Scale AI Theodore Papamarkou Maria Skoularidou Konstantina Palla Laurence Aitchison Julyan Arbel ... David Rügamer Yee Whye Teh Max Welling Andrew Gordon Wilson Ruqi Zhang UQCV BDL 24 27 0 01 Feb 2024
Accelerated Linearized Laplace Approximation for Bayesian Deep Learning Zhijie Deng Feng Zhou Jun Zhu BDL 34 13 0 23 Oct 2022
Multiwavelet-based Operator Learning for Differential Equations Gaurav Gupta Xiongye Xiao P. Bogdan 115 198 0 28 Sep 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
Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam Mohammad Emtiyaz Khan Didrik Nielsen Voot Tangkaratt Wu Lin Y. Gal Akash Srivastava ODL 71 264 0 13 Jun 2018
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 243 9,042 0 06 Jun 2015