Scaling-up Diverse Orthogonal Convolutional Networks with a Paraunitary
Framework

Scaling-up Diverse Orthogonal Convolutional Networks with a Paraunitary Framework

16 June 2021

Furong Huang

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Papers citing "Scaling-up Diverse Orthogonal Convolutional Networks with a Paraunitary Framework"

6 / 6 papers shown

Title
Parseval Convolution Operators and Neural Networks Michael Unser Stanislas Ducotterd 153 4 0 19 Aug 2024
Group Orthogonalization Regularization For Vision Models Adaptation and RobustnessBritish Machine Vision Conference (BMVC), 2023 Yoav Kurtz Noga Bar Raja Giryes 225 1 0 16 Jun 2023
Robust One-Class Classification with Signed Distance Function using 1-Lipschitz Neural NetworksInternational Conference on Machine Learning (ICML), 2023 Louis Bethune Paul Novello Thibaut Boissin Guillaume Coiffier M. Serrurier Quentin Vincenot Andres Troya-Galvis 223 11 0 26 Jan 2023
Improved techniques for deterministic l2 robustnessNeural Information Processing Systems (NeurIPS), 2022 Sahil Singla Soheil Feizi AAML 176 11 0 15 Nov 2022
Certified Defense via Latent Space Randomized Smoothing with Orthogonal Encoders Huimin Zeng Jiahao Su Furong Huang AAML 89 4 0 01 Aug 2021
Pay attention to your loss: understanding misconceptions about 1-Lipschitz neural networksNeural Information Processing Systems (NeurIPS), 2021 Louis Bethune Thibaut Boissin M. Serrurier Franck Mamalet Corentin Friedrich Alberto González Sanz 352 29 0 11 Apr 2021