Some Fundamental Aspects about Lipschitz Continuity of Neural Networks

21 February 2023

Papers citing "Some Fundamental Aspects about Lipschitz Continuity of Neural Networks"

8 / 8 papers shown

Title
RaanA: A Fast, Flexible, and Data-Efficient Post-Training Quantization Algorithm Yongyi Yang Jianyang Gao Wei Hu MQ 31 1 0 29 Mar 2025
Deterministic Uncertainty Propagation for Improved Model-Based Offline Reinforcement Learning Abdullah Akgul Manuel Haußmann M. Kandemir OffRL 64 1 0 17 Jan 2025
Training Free Guided Flow Matching with Optimal Control Luran Wang Chaoran Cheng Yizhen Liao Yanru Qu Ge Liu 31 1 0 23 Oct 2024
Ferrari: Federated Feature Unlearning via Optimizing Feature Sensitivity Hanlin Gu W. Ong Chee Seng Chan Lixin Fan MU 23 7 0 23 May 2024
A Wasserstein perspective of Vanilla GANs Lea Kunkel Mathias Trabs 16 3 0 22 Mar 2024
Why neural networks find simple solutions: the many regularizers of geometric complexity Benoit Dherin Michael Munn M. Rosca David Barrett 53 30 0 27 Sep 2022
Globally-Robust Neural Networks Klas Leino Zifan Wang Matt Fredrikson AAML OOD 80 125 0 16 Feb 2021
Adversarial Machine Learning at Scale Alexey Kurakin Ian Goodfellow Samy Bengio AAML 256 3,102 0 04 Nov 2016