A Quantitative Geometric Approach to Neural-Network Smoothness

2 March 2022

Papers citing "A Quantitative Geometric Approach to Neural-Network Smoothness"

6 / 6 papers shown

Title
Improved Scalable Lipschitz Bounds for Deep Neural Networks U. Syed Bin Hu BDL 56 0 0 18 Mar 2025
Monotone, Bi-Lipschitz, and Polyak-Lojasiewicz Networks Ruigang Wang Krishnamurthy Dvijotham I. Manchester 36 5 0 02 Feb 2024
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
Introduction to Neural Network Verification Aws Albarghouthi AAML 53 85 0 21 Sep 2021
Globally-Robust Neural Networks Klas Leino Zifan Wang Matt Fredrikson AAML OOD 80 125 0 16 Feb 2021
Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks Guy Katz Clark W. Barrett D. Dill Kyle D. Julian Mykel Kochenderfer AAML 249 1,838 0 03 Feb 2017