Approximating Lipschitz continuous functions with GroupSort neural networks

9 June 2020

Papers citing "Approximating Lipschitz continuous functions with GroupSort neural networks"

10 / 10 papers shown

Title
Fast and scalable Wasserstein-1 neural optimal transport solver for single-cell perturbation prediction Yanshuo Chen Zhengmian Hu Wei Chen Heng Huang OT 55 2 0 01 Nov 2024
Convolutional Neural Networks as 2-D systems Dennis Gramlich Patricia Pauli C. Scherer Frank Allgöwer C. Ebenbauer 3DV 36 8 0 06 Mar 2023
Robust One-Class Classification with Signed Distance Function using 1-Lipschitz Neural Networks Louis Bethune Paul Novello Thibaut Boissin Guillaume Coiffier M. Serrurier Quentin Vincenot Andres Troya-Galvis 36 8 0 26 Jan 2023
Impossibility Theorems for Feature Attribution Blair Bilodeau Natasha Jaques Pang Wei Koh Been Kim FAtt 25 68 0 22 Dec 2022
On the Number of Regions of Piecewise Linear Neural Networks Alexis Goujon Arian Etemadi M. Unser 49 14 0 17 Jun 2022
Deep Generative Survival Analysis: Nonparametric Estimation of Conditional Survival Function Xing Zhou Wen Su Changyu Liu Yuling Jiao Xingqiu Zhao Jian Huang CML MedIm 35 4 0 19 May 2022
Approximation of Lipschitz Functions using Deep Spline Neural Networks Sebastian Neumayer Alexis Goujon Pakshal Bohra M. Unser 45 16 0 13 Apr 2022
Generative Modeling with Optimal Transport Maps Litu Rout Alexander Korotin Evgeny Burnaev OT DiffM 122 65 0 06 Oct 2021
Wasserstein Generative Adversarial Uncertainty Quantification in Physics-Informed Neural Networks Yihang Gao Michael K. Ng 38 29 0 30 Aug 2021
Benefits of depth in neural networks Matus Telgarsky 155 603 0 14 Feb 2016