Orthogonalizing Convolutional Layers with the Cayley Transform

14 April 2021

J. Zico Kolter

Papers citing "Orthogonalizing Convolutional Layers with the Cayley Transform"

28 / 28 papers shown

Title
Bridging the Theoretical Gap in Randomized Smoothing Blaise Delattre Paul Caillon Quentin Barthélemy Erwan Fagnou Alexandre Allauzen AAML 53 0 0 03 Apr 2025
Fast and scalable Wasserstein-1 neural optimal transport solver for single-cell perturbation prediction Yanshuo Chen Zhengmian Hu Wei Chen Heng Huang OT 47 1 0 01 Nov 2024
Certified Causal Defense with Generalizable Robustness Yiran Qiao Yu Yin Chen Chen Jing Ma AAML OOD CML 52 0 0 28 Aug 2024
Parseval Convolution Operators and Neural Networks Michael Unser Stanislas Ducotterd 23 3 0 19 Aug 2024
1-Lipschitz Neural Distance Fields Guillaume Coiffier Louis Bethune 43 3 0 14 Jun 2024
On Robust Reinforcement Learning with Lipschitz-Bounded Policy Networks Nicholas H. Barbara Ruigang Wang I. Manchester 35 4 0 19 May 2024
Graph Unitary Message Passing Haiquan Qiu Yatao Bian Quanming Yao 34 2 0 17 Mar 2024
Monotone, Bi-Lipschitz, and Polyak-Lojasiewicz Networks Ruigang Wang Krishnamurthy Dvijotham I. Manchester 29 5 0 02 Feb 2024
1-Lipschitz Neural Networks are more expressive with N-Activations Bernd Prach Christoph H. Lampert AAML FAtt 24 0 0 10 Nov 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
Robust low-rank training via approximate orthonormal constraints Dayana Savostianova Emanuele Zangrando Gianluca Ceruti Francesco Tudisco 24 9 0 02 Jun 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
Orthogonal SVD Covariance Conditioning and Latent Disentanglement Yue Song N. Sebe Wei Wang 26 6 0 11 Dec 2022
Improved techniques for deterministic l2 robustness Sahil Singla S. Feizi AAML 23 9 0 15 Nov 2022
Dynamical systems' based neural networks E. Celledoni Davide Murari B. Owren Carola-Bibiane Schönlieb Ferdia Sherry OOD 40 10 0 05 Oct 2022
Almost-Orthogonal Layers for Efficient General-Purpose Lipschitz Networks Bernd Prach Christoph H. Lampert 32 35 0 05 Aug 2022
Provably Adversarially Robust Nearest Prototype Classifiers Václav Voráček Matthias Hein AAML 20 11 0 14 Jul 2022
Improving Covariance Conditioning of the SVD Meta-layer by Orthogonality Yue Song N. Sebe Wei Wang 16 8 0 05 Jul 2022
Efficiently Training Low-Curvature Neural Networks Suraj Srinivas Kyle Matoba Himabindu Lakkaraju F. Fleuret AAML 23 15 0 14 Jun 2022
Towards Evading the Limits of Randomized Smoothing: A Theoretical Analysis Raphael Ettedgui Alexandre Araujo Rafael Pinot Y. Chevaleyre Jamal Atif AAML 32 3 0 03 Jun 2022
Feedback Gradient Descent: Efficient and Stable Optimization with Orthogonality for DNNs Fanchen Bu D. Chang 17 6 0 12 May 2022
projUNN: efficient method for training deep networks with unitary matrices B. Kiani Randall Balestriero Yann LeCun S. Lloyd 36 32 0 10 Mar 2022
Orthogonal Graph Neural Networks Kai Guo Kaixiong Zhou Xia Hu Yu Li Yi Chang Xin Wang 43 34 0 23 Sep 2021
Existence, Stability and Scalability of Orthogonal Convolutional Neural Networks E. M. Achour Franccois Malgouyres Franck Mamalet 16 20 0 12 Aug 2021
Dirichlet Energy Constrained Learning for Deep Graph Neural Networks Kaixiong Zhou Xiao Shi Huang Daochen Zha Rui Chen Li Li Soo-Hyun Choi Xia Hu GNN AI4CE 22 114 0 06 Jul 2021
Dynamical Isometry and a Mean Field Theory of CNNs: How to Train 10,000-Layer Vanilla Convolutional Neural Networks Lechao Xiao Yasaman Bahri Jascha Narain Sohl-Dickstein S. Schoenholz Jeffrey Pennington 220 348 0 14 Jun 2018
Safety Verification of Deep Neural Networks Xiaowei Huang M. Kwiatkowska Sen Wang Min Wu AAML 180 932 0 21 Oct 2016