Neural Stochastic PDEs: Resolution-Invariant Learning of Continuous Spatiotemporal Dynamics

19 October 2021

Papers citing "Neural Stochastic PDEs: Resolution-Invariant Learning of Continuous Spatiotemporal Dynamics"

9 / 9 papers shown

Title
Deep Optimal Sensor Placement for Black Box Stochastic Simulations Paula Cordero-Encinar Tobias Schröder P. Yatsyshin Andrew Duncan 45 0 0 15 Oct 2024
Learning with SASQuaTCh: a Novel Variational Quantum Transformer Architecture with Kernel-Based Self-Attention Ethan N. Evans Matthew G. Cook Zachary P. Bradshaw Margarite L. LaBorde 40 5 0 21 Mar 2024
Theoretical Foundations of Deep Selective State-Space Models Nicola Muca Cirone Antonio Orvieto Benjamin Walker C. Salvi Terry Lyons Mamba 53 25 0 29 Feb 2024
Investigating the Ability of PINNs To Solve Burgers' PDE Near Finite-Time BlowUp Dibyakanti Kumar Anirbit Mukherjee 31 2 0 08 Oct 2023
On the Parallel Complexity of Multilevel Monte Carlo in Stochastic Gradient Descent Kei Ishikawa BDL 58 0 0 03 Oct 2023
Solving Inverse Physics Problems with Score Matching Benjamin Holzschuh S. Vegetti Nils Thuerey DiffM 11 9 0 24 Jan 2023
Towards Size-Independent Generalization Bounds for Deep Operator Nets Pulkit Gopalani Sayar Karmakar Dibyakanti Kumar Anirbit Mukherjee AI4CE 24 5 0 23 May 2022
Feature Engineering with Regularity Structures I. Chevyrev A. Gerasimovičs H. Weber 25 10 0 12 Aug 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 203 2,282 0 18 Oct 2020