176 citations · 467 across the 10 of their papers we have counts for
3 papers · 1 filter
Asymptotically unbiased estimation of physical observables with neural samplers
Kim A. Nicoli, Shinichi Nakajima, Nils Strodthoff +3
We propose a general framework for the estimation of observables with generative neural samplers focusing on modern deep generative neural networks that provide an exact sampling p…
Achieving Generalizable Robustness of Deep Neural Networks by Stability Training
Jan Laermann, Wojciech Samek, Nils Strodthoff
We study the recently introduced stability training as a general-purpose method to increase the robustness of deep neural networks against input perturbations. In particular, we ex…
Comment on "Solving Statistical Mechanics Using VANs": Introducing saVANt - VANs Enhanced by Importance and MCMC Sampling
Kim Nicoli, Pan Kessel, Nils Strodthoff +3
In this comment on "Solving Statistical Mechanics Using Variational Autoregressive Networks" by Wu et al., we propose a subtle yet powerful modification of their approach. We show…