29 citations · 30 across the 3 of their papers we have counts for
3 papers
cs.LG2025
Lagrangian neural ODEs: Measuring the existence of a Lagrangian with Helmholtz metrics
Luca Wolf, Tobias Buck, Bjoern Malte Schaefer
Neural ODEs are a widely used, powerful machine learning technique in particular for physics. However, not every solution is physical in that it is an Euler-Lagrange equation. We p…
astro-ph.GA2023★ 1 cited
GalacticFlow: Learning a Generalized Representation of Galaxies with Normalizing Flows
Luca Wolf, Tobias Buck
State-of-the-art galaxy formation simulations generate data within weeks or months. Their results consist of a random sub-sample of possible galaxies with a fixed number of stars.…
quant-ph2022★ 29 cited
Uncovering Instabilities in Variational-Quantum Deep Q-Networks
Maja Franz, Lucas Wolf, Maniraman Periyasamy +5
Deep Reinforcement Learning (RL) has considerably advanced over the past decade. At the same time, state-of-the-art RL algorithms require a large computational budget in terms of t…