Henrik Schopmans

According to our database, Henrik Schopmans authored at least 9 papers between 2022 and 2026.

Collaborative distances:

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

2026

Efficient Training of Boltzmann Generators Using Off-Policy Log-Dispersion Regularization.

Henrik Schopmans, Christopher von Klitzing, Pascal Friederich

CoRR, February, 2026

2025

Generative models for crystalline materials.

Houssam Metni, Laura Ruple, Lauren N. Walters, Luca Torresi, Jonas Teufel, Henrik Schopmans, Jona Östreicher, Yumeng Zhang, Marlen Neubert, Yuri Koide, Kevin Steiner, Paul Link, Lukas Bär, Mariana Petrova, Gerbrand Ceder, Pascal Friederich

CoRR, November, 2025

Learning Boltzmann Generators via Constrained Mass Transport.

Christopher von Klitzing, Denis Blessing, Henrik Schopmans, Pascal Friederich, Gerhard Neumann

CoRR, October, 2025

opXRD: Open Experimental Powder X-ray Diffraction Database.

Daniel Hollarek, Henrik Schopmans, Jona Östreicher, Jonas Teufel, Bin Cao, Adie Alwen, Simon Schweidler, Mriganka Singh, Tim Kodalle, Hanlin Hu, Gregoire Heymans, Maged Abdelsamie, Arthur Hardiagon, Alexander Wieczorek, Siarhei Zhuk, Ruth Schwaiger, Sebastian Siol, François-Xavier Coudert, Moritz Wolf, Carolin M. Sutter-Fella, Ben Breitung, Andrea M. Hodge, Tong-yi Zhang, Pascal Friederich

CoRR, March, 2025

Symmetry-Aware Bayesian Flow Networks for Crystal Generation.

Laura Ruple, Luca Torresi, Henrik Schopmans, Pascal Friederich

CoRR, February, 2025

Temperature-Annealed Boltzmann Generators.

Henrik Schopmans, Pascal Friederich

Proceedings of the Forty-second International Conference on Machine Learning, 2025

2024

Conditional Normalizing Flows for Active Learning of Coarse-Grained Molecular Representations.

Henrik Schopmans, Pascal Friederich

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

Neural networks trained on synthetically generated crystals can extract structural information from ICSD powder X-ray diffractograms.

Henrik Schopmans, Patrick Reiser, Pascal Friederich

CoRR, 2023

2022

Graph neural networks for materials science and chemistry.

Patrick Reiser, Marlen Neubert, André Eberhard, Luca Torresi, Chen Zhou, Chen Shao, Houssam Metni, Clint van Hoesel, Henrik Schopmans, Timo Sommer, Pascal Friederich

CoRR, 2022