Sorting out Lipschitz function approximation

13 November 2018

Papers citing "Sorting out Lipschitz function approximation"

50 / 73 papers shown

Title
Approximation theory for 1-Lipschitz ResNets Davide Murari Takashi Furuya Carola-Bibiane Schönlieb 9 0 0 17 May 2025
A Formally Verified Robustness Certifier for Neural Networks (Extended Version) James Tobler Hira Taqdees Syeda Toby Murray AAML 29 0 0 11 May 2025
Probabilistic Stability Guarantees for Feature Attributions Helen Jin Anton Xue Weiqiu You Surbhi Goel Eric Wong 27 0 0 18 Apr 2025
Support is All You Need for Certified VAE Training Changming Xu Debangshu Banerjee Deepak Vasisht Gagandeep Singh AAML 44 0 0 16 Apr 2025
On Space Folds of ReLU Neural Networks Michal Lewandowski Hamid Eghbalzadeh Bernhard Heinzl Raphael Pisoni Bernhard A.Moser MLT 87 1 0 17 Feb 2025
HadamRNN: Binary and Sparse Ternary Orthogonal RNNs Armand Foucault Franck Mamalet François Malgouyres MQ 85 0 0 28 Jan 2025
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
Certified Causal Defense with Generalizable Robustness Yiran Qiao Yu Yin Chen Chen Jing Ma AAML OOD CML 63 0 0 28 Aug 2024
JacNet: Learning Functions with Structured Jacobians Jonathan Lorraine Safwan Hossain 48 6 0 23 Aug 2024
Parseval Convolution Operators and Neural Networks Michael Unser Stanislas Ducotterd 25 3 0 19 Aug 2024
Hidden Synergy: $L_1$ Weight Normalization and 1-Path-Norm Regularization Aditya Biswas 41 0 0 29 Apr 2024
Input Convex Lipschitz RNN: A Fast and Robust Approach for Engineering Tasks Zihao Wang Zhe Wu 25 3 0 15 Jan 2024
How Smooth Is Attention? Valérie Castin Pierre Ablin Gabriel Peyré AAML 40 9 0 22 Dec 2023
Spatial Bayesian Neural Networks A. Zammit‐Mangion Michael D. Kaminski Ba-Hien Tran Maurizio Filippone Noel Cressie BDL 18 7 0 16 Nov 2023
1-Lipschitz Neural Networks are more expressive with N-Activations Bernd Prach Christoph H. Lampert AAML FAtt 24 0 0 10 Nov 2023
Fair Wasserstein Coresets Zikai Xiong Niccolò Dalmasso Shubham Sharma Freddy Lecue Daniele Magazzeni Vamsi K. Potluru T. Balch Manuela Veloso 34 2 0 09 Nov 2023
Function-Space Optimality of Neural Architectures with Multivariate Nonlinearities Rahul Parhi Michael Unser 47 5 0 05 Oct 2023
Certified Robustness via Dynamic Margin Maximization and Improved Lipschitz Regularization Mahyar Fazlyab Taha Entesari Aniket Roy Ramalingam Chellappa AAML 16 11 0 29 Sep 2023
Certified Robust Models with Slack Control and Large Lipschitz Constants M. Losch David Stutz Bernt Schiele Mario Fritz 14 4 0 12 Sep 2023
Performance Scaling via Optimal Transport: Enabling Data Selection from Partially Revealed Sources Feiyang Kang H. Just Anit Kumar Sahu R. Jia 61 10 0 05 Jul 2023
Finding Counterfactually Optimal Action Sequences in Continuous State Spaces Stratis Tsirtsis Manuel Gomez Rodriguez CML OffRL 30 9 0 06 Jun 2023
Robust low-rank training via approximate orthonormal constraints Dayana Savostianova Emanuele Zangrando Gianluca Ceruti Francesco Tudisco 26 9 0 02 Jun 2023
PDE+: Enhancing Generalization via PDE with Adaptive Distributional Diffusion Yige Yuan Bingbing Xu Bo Lin Liang Hou Fei Sun Huawei Shen Xueqi Cheng DiffM 26 4 0 25 May 2023
When Deep Learning Meets Polyhedral Theory: A Survey Joey Huchette Gonzalo Muñoz Thiago Serra Calvin Tsay AI4CE 94 32 0 29 Apr 2023
Lipschitz-bounded 1D convolutional neural networks using the Cayley transform and the controllability Gramian Patricia Pauli Ruigang Wang I. Manchester Frank Allgöwer 32 8 0 20 Mar 2023
A Unified Algebraic Perspective on Lipschitz Neural Networks Alexandre Araujo Aaron J. Havens Blaise Delattre A. Allauzen Bin Hu AAML 36 52 0 06 Mar 2023
Convolutional Neural Networks as 2-D systems Dennis Gramlich Patricia Pauli C. Scherer Frank Allgöwer C. Ebenbauer 3DV 36 8 0 06 Mar 2023
CQnet: convex-geometric interpretation and constraining neural-network trajectories Bas Peters 35 0 0 09 Feb 2023
A Neural-Network-Based Convex Regularizer for Inverse Problems Alexis Goujon Sebastian Neumayer Pakshal Bohra Stanislas Ducotterd M. Unser 19 26 0 22 Nov 2022
Improved techniques for deterministic l2 robustness Sahil Singla S. Feizi AAML 23 9 0 15 Nov 2022
Instance-Dependent Generalization Bounds via Optimal Transport Songyan Hou Parnian Kassraie Anastasis Kratsios Andreas Krause Jonas Rothfuss 22 6 0 02 Nov 2022
Improving Lipschitz-Constrained Neural Networks by Learning Activation Functions Stanislas Ducotterd Alexis Goujon Pakshal Bohra Dimitris Perdios Sebastian Neumayer M. Unser 35 12 0 28 Oct 2022
Certified Training: Small Boxes are All You Need Mark Niklas Muller Franziska Eckert Marc Fischer Martin Vechev AAML 39 45 0 10 Oct 2022
Dynamical systems' based neural networks E. Celledoni Davide Murari B. Owren Carola-Bibiane Schönlieb Ferdia Sherry OOD 46 12 0 05 Oct 2022
Finding NEEMo: Geometric Fitting using Neural Estimation of the Energy Mover's Distance O. Kitouni Niklas Nolte Mike Williams 26 8 0 30 Sep 2022
Almost-Orthogonal Layers for Efficient General-Purpose Lipschitz Networks Bernd Prach Christoph H. Lampert 32 35 0 05 Aug 2022
On the Number of Regions of Piecewise Linear Neural Networks Alexis Goujon Arian Etemadi M. Unser 44 13 0 17 Jun 2022
A Simple Approach to Improve Single-Model Deep Uncertainty via Distance-Awareness J. Liu Shreyas Padhy Jie Jessie Ren Zi Lin Yeming Wen Ghassen Jerfel Zachary Nado Jasper Snoek Dustin Tran Balaji Lakshminarayanan UQCV BDL 26 48 0 01 May 2022
Approximation of Lipschitz Functions using Deep Spline Neural Networks Sebastian Neumayer Alexis Goujon Pakshal Bohra M. Unser 37 16 0 13 Apr 2022
Input Convex Gradient Networks Jack Richter-Powell Jonathan Lorraine Brandon Amos 14 15 0 23 Nov 2021
GraN-GAN: Piecewise Gradient Normalization for Generative Adversarial Networks Vineeth S. Bhaskara Tristan Aumentado-Armstrong Allan D. Jepson Alex Levinshtein GAN 43 5 0 04 Nov 2021
Training Certifiably Robust Neural Networks with Efficient Local Lipschitz Bounds Yujia Huang Huan Zhang Yuanyuan Shi J Zico Kolter Anima Anandkumar 38 76 0 02 Nov 2021
Logical Activation Functions: Logit-space equivalents of Probabilistic Boolean Operators S. Lowe Robert C. Earle Jason dÉon Thomas Trappenberg Sageev Oore 23 1 0 22 Oct 2021
Generative Modeling with Optimal Transport Maps Litu Rout Alexander Korotin Evgeny Burnaev OT DiffM 122 65 0 06 Oct 2021
CC-Cert: A Probabilistic Approach to Certify General Robustness of Neural Networks Mikhail Aleksandrovich Pautov Nurislam Tursynbek Marina Munkhoeva Nikita Muravev Aleksandr Petiushko Ivan Oseledets AAML 52 16 0 22 Sep 2021
An automatic differentiation system for the age of differential privacy Dmitrii Usynin Alexander Ziller Moritz Knolle Andrew Trask Kritika Prakash Daniel Rueckert Georgios Kaissis 30 3 0 22 Sep 2021
Wasserstein Generative Adversarial Uncertainty Quantification in Physics-Informed Neural Networks Yihang Gao Michael K. Ng 38 28 0 30 Aug 2021
Existence, Stability and Scalability of Orthogonal Convolutional Neural Networks E. M. Achour Franccois Malgouyres Franck Mamalet 16 20 0 12 Aug 2021
Spectral Normalisation for Deep Reinforcement Learning: an Optimisation Perspective Florin Gogianu Tudor Berariu Mihaela Rosca Claudia Clopath L. Buşoniu Razvan Pascanu 24 52 0 11 May 2021
Neural Network Robustness as a Verification Property: A Principled Case Study Marco Casadio Ekaterina Komendantskaya M. Daggitt Wen Kokke Guy Katz Guy Amir Idan Refaeli OOD AAML 16 39 0 03 Apr 2021