Stephan Thaler

According to our database, Stephan Thaler authored at least 9 papers between 2019 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

chemtrain-deploy: A parallel and scalable framework for machine learning potentials in million-atom MD simulations.

Paul Fuchs, Weilong Chen, Stephan Thaler, Julija Zavadlav

CoRR, June, 2025

chemtrain: Learning deep potential models via automatic differentiation and statistical physics.

Paul Fuchs, Stephan Thaler, Sebastien Röcken, Julija Zavadlav

Comput. Phys. Commun., 2025

2024

JaxSGMC: Modular stochastic gradient MCMC in JAX.

Stephan Thaler, Paul Fuchs, Ana Cukarska, Julija Zavadlav

SoftwareX, 2024

Implicit Delta Learning of High Fidelity Neural Network Potentials.

Stephan Thaler, Cristian Gabellini, Nikhil Shenoy, Prudencio Tossou

CoRR, 2024

OpenQDC: Open Quantum Data Commons.

Cristian Gabellini, Nikhil Shenoy, Stephan Thaler, Semih Cantürk, Daniel McNeela, Dominique Beaini, Michael M. Bronstein, Prudencio Tossou

CoRR, 2024

ET-Flow: Equivariant Flow-Matching for Molecular Conformer Generation.

Majdi Hassan, Nikhil Shenoy, Jungyoon Lee, Hannes Stärk, Stephan Thaler, Dominique Beaini

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

2022

Scalable Bayesian Uncertainty Quantification for Neural Network Potentials: Promise and Pitfalls.

Stephan Thaler, Gregor Doehner, Julija Zavadlav

CoRR, 2022

2021

Learning neural network potentials from experimental data via Differentiable Trajectory Reweighting.

Stephan Thaler, Julija Zavadlav

CoRR, 2021

2019

Sparse identification of truncation errors.

Stephan Thaler, Ludger Paehler, Nikolaus A. Adams

J. Comput. Phys., 2019