36 citations · 55 across the 9 of their papers we have counts for
3 papers · 1 filter
Weight Space Representation Learning via Neural Field Adaptation
Zhuoqian Yang, Mathieu Salzmann, Sabine Süsstrunk
We investigate the potential of weights to serve as effective representations, focusing on neural fields. Our key insight is that constraining the optimization space through a pre-…
On the Loss Landscape of Adversarial Training: Identifying Challenges and How to Overcome Them
Chen Liu, Mathieu Salzmann, Tao Lin +2
We analyze the influence of adversarial training on the loss landscape of machine learning models. To this end, we first provide analytical studies of the properties of adversarial…
Training Provably Robust Models by Polyhedral Envelope Regularization
Chen Liu, Mathieu Salzmann, Sabine Süsstrunk
Training certifiable neural networks enables one to obtain models with robustness guarantees against adversarial attacks. In this work, we introduce a framework to bound the advers…