Nonlinear Approximation and (Deep) ReLU Networks

5 May 2019

Papers citing "Nonlinear Approximation and (Deep) ReLU Networks"

22 / 22 papers shown

Title
Deep Kalman Filters Can Filter Blanka Hovart Anastasis Kratsios Yannick Limmer Xuwei Yang 45 1 0 31 Dec 2024
Fast and Exact Enumeration of Deep Networks Partitions Regions Randall Balestriero Yann LeCun 18 5 0 20 Jan 2024
Mathematical Algorithm Design for Deep Learning under Societal and Judicial Constraints: The Algorithmic Transparency Requirement Holger Boche Adalbert Fono Gitta Kutyniok FaML 31 4 0 18 Jan 2024
Parameter-varying neural ordinary differential equations with partition-of-unity networks Kookjin Lee N. Trask 22 2 0 01 Oct 2022
CP-PINNs: Data-Driven Changepoints Detection in PDEs Using Online Optimized Physics-Informed Neural Networks Zhi-Ling Dong Pawel Polak PINN 21 1 0 18 Aug 2022
Sparse Deep Neural Network for Nonlinear Partial Differential Equations Yuesheng Xu T. Zeng 30 5 0 27 Jul 2022
Approximation of functions with one-bit neural networks C. S. Güntürk Weilin Li 17 8 0 16 Dec 2021
Sobolev-type embeddings for neural network approximation spaces Philipp Grohs F. Voigtlaender 14 1 0 28 Oct 2021
Designing Rotationally Invariant Neural Networks from PDEs and Variational Methods Tobias Alt Karl Schrader Joachim Weickert Pascal Peter M. Augustin 22 4 0 31 Aug 2021
Neural Network Approximation of Refinable Functions Ingrid Daubechies Ronald A. DeVore Nadav Dym Shira Faigenbaum-Golovin S. Kovalsky Kung-Chin Lin Josiah Park G. Petrova B. Sober 23 14 0 28 Jul 2021
High-Dimensional Distribution Generation Through Deep Neural Networks Dmytro Perekrestenko Léandre Eberhard Helmut Bölcskei OOD 27 6 0 26 Jul 2021
Deep Network Approximation: Achieving Arbitrary Accuracy with Fixed Number of Neurons Zuowei Shen Haizhao Yang Shijun Zhang 48 36 0 06 Jul 2021
Random Neural Networks in the Infinite Width Limit as Gaussian Processes Boris Hanin BDL 24 43 0 04 Jul 2021
A Deep Learning approach to Reduced Order Modelling of Parameter Dependent Partial Differential Equations N. R. Franco Andrea Manzoni P. Zunino 18 45 0 10 Mar 2021
Stochastic Markov Gradient Descent and Training Low-Bit Neural Networks Jonathan Ashbrock A. Powell MQ 28 5 0 25 Aug 2020
Approximation of Smoothness Classes by Deep Rectifier Networks Mazen Ali A. Nouy 9 9 0 30 Jul 2020
Depth separation for reduced deep networks in nonlinear model reduction: Distilling shock waves in nonlinear hyperbolic problems Donsub Rim Luca Venturi Joan Bruna Benjamin Peherstorfer 17 9 0 28 Jul 2020
Variational Physics-Informed Neural Networks For Solving Partial Differential Equations E. Kharazmi Z. Zhang George Karniadakis 16 236 0 27 Nov 2019
Universal Approximation with Deep Narrow Networks Patrick Kidger Terry Lyons 27 324 0 21 May 2019
Mad Max: Affine Spline Insights into Deep Learning Randall Balestriero Richard Baraniuk AI4CE 31 78 0 17 May 2018
Geometric deep learning: going beyond Euclidean data M. Bronstein Joan Bruna Yann LeCun Arthur Szlam P. Vandergheynst GNN 253 3,239 0 24 Nov 2016
Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation Yonghui Wu M. Schuster Z. Chen Quoc V. Le Mohammad Norouzi ... Alex Rudnick Oriol Vinyals G. Corrado Macduff Hughes J. Dean AIMat 716 6,743 0 26 Sep 2016