118 citations · 280 across the 17 of their papers we have counts for
3 papers · 1 filter
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…
Modern applications of machine learning in quantum sciences
Anna Dawid, Julian Arnold, Borja Requena +26
In this book, we provide a comprehensive introduction to the most recent advances in the application of machine learning methods in quantum sciences. We cover the use of deep learn…