Stateful ODE-Nets using Basis Function Expansions

21 June 2021

Papers citing "Stateful ODE-Nets using Basis Function Expansions"

7 / 7 papers shown

Title
Elucidating the Design Choice of Probability Paths in Flow Matching for Forecasting S. H. Lim Yijin Wang Annan Yu Emma Hart Michael W. Mahoney Xiaoye S. Li N. Benjamin Erichson AI4TS 42 1 0 04 Oct 2024
Parameter-varying neural ordinary differential equations with partition-of-unity networks Kookjin Lee N. Trask 22 2 0 01 Oct 2022
Noisy Learning for Neural ODEs Acts as a Robustness Locus Widening Martin Gonzalez H. Hajri Loic Cantat M. Petreczky 27 1 0 16 Jun 2022
Standalone Neural ODEs with Sensitivity Analysis Rym Jaroudi Lukáš Malý Gabriel Eilertsen B. Johansson Jonas Unger George Baravdish 16 0 0 27 May 2022
Learning continuous models for continuous physics Aditi S. Krishnapriyan A. Queiruga N. Benjamin Erichson Michael W. Mahoney AI4CE 18 32 0 17 Feb 2022
Characteristic Neural Ordinary Differential Equations Xingzi Xu Ali Hasan Khalil Elkhalil Jie Ding Vahid Tarokh BDL 19 3 0 25 Nov 2021
Lagrangian Neural Networks M. Cranmer S. Greydanus Stephan Hoyer Peter W. Battaglia D. Spergel S. Ho PINN 121 419 0 10 Mar 2020