Predictions Based on Pixel Data: Insights from PDEs and Finite Differences

1 May 2023

Papers citing "Predictions Based on Pixel Data: Insights from PDEs and Finite Differences"

8 / 8 papers shown

Title
Exactly conservative physics-informed neural networks and deep operator networks for dynamical systems E. Cardoso-Bihlo Alex Bihlo AI4CE PINN 31 5 0 23 Nov 2023
Pseudo-Hamiltonian neural networks for learning partial differential equations Sølve Eidnes K. Lye 16 10 0 27 Apr 2023
Dynamical systems' based neural networks E. Celledoni Davide Murari B. Owren Carola-Bibiane Schönlieb Ferdia Sherry OOD 32 10 0 05 Oct 2022
Learning Hamiltonians of constrained mechanical systems E. Celledoni A. Leone Davide Murari B. Owren AI4CE 29 17 0 31 Jan 2022
Primer: Searching for Efficient Transformers for Language Modeling David R. So Wojciech Mañke Hanxiao Liu Zihang Dai Noam M. Shazeer Quoc V. Le VLM 83 151 0 17 Sep 2021
Curriculum Learning: A Survey Petru Soviany Radu Tudor Ionescu Paolo Rota N. Sebe ODL 63 337 0 25 Jan 2021
Symplectic Recurrent Neural Networks Zhengdao Chen Jianyu Zhang Martín Arjovsky Léon Bottou 139 219 0 29 Sep 2019
$Approximation by Combinations of ReLU and Squared ReLU Ridge Functions with $ \ell^1 $ and $ \ell^0 $ Controls$ Approximation by Combinations of ReLU and Squared ReLU Ridge Functions with $\ell^1$ and $\ell^0$ Controls Jason M. Klusowski Andrew R. Barron 122 142 0 26 Jul 2016