456 citations · 955 across the 15 of their papers we have counts for
4 papers · 1 filter
Learning Trivializing Gradient Flows for Lattice Gauge Theories
Simone Bacchio, Pan Kessel, Stefan Schaefer +1
We propose a unifying approach that starts from the perturbative construction of trivializing maps by Lüscher and then improves on it by learning. The resulting continuous normaliz…
Gradients should stay on Path: Better Estimators of the Reverse- and Forward KL Divergence for Normalizing Flows
Lorenz Vaitl, Kim A. Nicoli, Shinichi Nakajima +1
We propose an algorithm to estimate the path-gradient of both the reverse and forward Kullback-Leibler divergence for an arbitrary manifestly invertible normalizing flow. The resul…
Path-Gradient Estimators for Continuous Normalizing Flows
Lorenz Vaitl, Kim A. Nicoli, Shinichi Nakajima +1
Recent work has established a path-gradient estimator for simple variational Gaussian distributions and has argued that the path-gradient is particularly beneficial in the regime i…
Diffeomorphic Counterfactuals with Generative Models
Ann-Kathrin Dombrowski, Jan E. Gerken, Klaus-Robert Müller +1
Counterfactuals can explain classification decisions of neural networks in a human interpretable way. We propose a simple but effective method to generate such counterfactuals. Mor…