Learning epidemic trajectories through Kernel Operator Learning: from modelling to optimal control

17 April 2024

Papers citing "Learning epidemic trajectories through Kernel Operator Learning: from modelling to optimal control"

6 / 6 papers shown

Title
Kernel Methods are Competitive for Operator Learning Pau Batlle Matthieu Darcy Bamdad Hosseini H. Owhadi 58 40 0 26 Apr 2023
Kernel Regression with Infinite-Width Neural Networks on Millions of Examples Ben Adlam Jaehoon Lee Shreyas Padhy Zachary Nado Jasper Snoek 44 11 0 09 Mar 2023
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 453 2,384 0 18 Oct 2020
DeepONet: Learning nonlinear operators for identifying differential equations based on the universal approximation theorem of operators Lu Lu Pengzhan Jin George Karniadakis 198 2,108 0 08 Oct 2019
Gradient Descent Provably Optimizes Over-parameterized Neural Networks S. Du Xiyu Zhai Barnabás Póczós Aarti Singh MLT ODL 192 1,270 0 04 Oct 2018
Kernel Flows: from learning kernels from data into the abyss H. Owhadi G. Yoo 53 90 0 13 Aug 2018