1-Lipschitz Layers Compared: Memory, Speed, and Certifiable Robustness

28 November 2023

Papers citing "1-Lipschitz Layers Compared: Memory, Speed, and Certifiable Robustness"

5 / 5 papers shown

Title
1-Lipschitz Neural Networks are more expressive with N-Activations Bernd Prach Christoph H. Lampert AAML FAtt 24 0 0 10 Nov 2023
Robust-by-Design Classification via Unitary-Gradient Neural Networks Fabio Brau Giulio Rossolini Alessandro Biondi Giorgio Buttazzo AAML 34 5 0 09 Sep 2022
Globally-Robust Neural Networks Klas Leino Zifan Wang Matt Fredrikson AAML OOD 80 125 0 16 Feb 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 220 347 0 14 Jun 2018
Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks Guy Katz Clark W. Barrett D. Dill Kyle D. Julian Mykel Kochenderfer AAML 222 1,832 0 03 Feb 2017