Oliver T. Unke

According to our database, Oliver T. Unke authored at least 22 papers between 2017 and 2026.

Collaborative distances:

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

2026

Characterizing High-Capacity Janus Aminobenzene-Graphene Anode for Sodium-Ion Batteries with Machine Learning.

Claudia Islas-Vargas, L. Ricardo Montoya, Carlos A. Vital-José, Oliver T. Unke, Klaus-Robert Müller, Huziel E. Sauceda

CoRR, March, 2026

Learning Hamiltonian Flow Maps: Mean Flow Consistency for Large-Timestep Molecular Dynamics.

Winfried Ripken, Michael Plainer, Gregor Lied, J. Thorben Frank, Oliver T. Unke, Stefan Chmiela, Frank Noé, Klaus-Robert Müller

CoRR, January, 2026

2025

Control Variate Score Matching for Diffusion Models.

Khaled Kahouli, Romuald Elie, Klaus-Robert Müller, Quentin Berthet, Oliver T. Unke, Arnaud Doucet

CoRR, December, 2025

How simple can you go? An off-the-shelf transformer approach to molecular dynamics.

Max Eissler, Tim Korjakow, Stefan Ganscha, Oliver T. Unke, Klaus-Robert Müller, Stefan Gugler

CoRR, March, 2025

Enhancing Diffusion Models Efficiency by Disentangling Total-Variance and Signal-to-Noise Ratio.

Khaled Kahouli, Winfried Ripken, Stefan Gugler, Oliver T. Unke, Klaus-Robert Müller, Shinichi Nakajima

CoRR, February, 2025

Data from: The QCML dataset, Quantum chemistry reference data from 33.5M DFT and 14.7B semi-empirical calculations.

Stefan Ganscha, Oliver T. Unke, Daniel Ahlin, Hartmut Maennel, Sergii Kashubin, Klaus-Robert Müller

Dataset, 2025

Data from: The QCML dataset, Quantum chemistry reference data from 33.5M DFT and 14.7B semi-empirical calculations.

Stefan Ganscha, Oliver T. Unke, Daniel Ahlin, Hartmut Maennel, Sergii Kashubin, Klaus-Robert Müller

Dataset, 2025

Sampling 3D Molecular Conformers with Diffusion Transformers.

J. Thorben Frank, Winfried Ripken, Gregor Lied, Klaus-Robert Müller, Oliver T. Unke, Stefan Chmiela

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

2024

Euclidean Fast Attention: Machine Learning Global Atomic Representations at Linear Cost.

J. Thorben Frank, Stefan Chmiela, Klaus-Robert Müller, Oliver T. Unke

CoRR, 2024

Complete and Efficient Covariants for 3D Point Configurations with Application to Learning Molecular Quantum Properties.

Hartmut Maennel, Oliver T. Unke, Klaus-Robert Müller

CoRR, 2024

E3x: E(3)-Equivariant Deep Learning Made Easy.

Oliver T. Unke, Hartmut Maennel

CoRR, 2024

2023

From Peptides to Nanostructures: A Euclidean Transformer for Fast and Stable Machine Learned Force Fields.

J. Thorben Frank, Oliver T. Unke, Klaus-Robert Müller, Stefan Chmiela

CoRR, 2023

2022

So3krates - Self-attention for higher-order geometric interactions on arbitrary length-scales.

J. Thorben Frank, Oliver T. Unke, Klaus-Robert Müller

CoRR, 2022

Accurate Machine Learned Quantum-Mechanical Force Fields for Biomolecular Simulations.

Oliver T. Unke, Martin Stöhr, Stefan Ganscha, Thomas Unterthiner, Hartmut Maennel, Sergii Kashubin, Daniel Ahlin, Michael Gastegger, Leonardo Medrano Sandonas, Alexandre Tkatchenko, Klaus-Robert Müller

CoRR, 2022

Automatic Identification of Chemical Moieties.

Jonas Lederer, Michael Gastegger, Kristof T. Schütt, Michael Kampffmeyer, Klaus-Robert Müller, Oliver T. Unke

CoRR, 2022

So3krates: Equivariant attention for interactions on arbitrary length-scales in molecular systems.

J. Thorben Frank, Oliver T. Unke, Klaus-Robert Müller

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

SpookyNet: Learning Force Fields with Electronic Degrees of Freedom and Nonlocal Effects.

Oliver T. Unke, Stefan Chmiela, Michael Gastegger, Kristof T. Schütt, Huziel E. Sauceda, Klaus-Robert Müller

CoRR, 2021

SE(3)-equivariant prediction of molecular wavefunctions and electronic densities.

Oliver T. Unke, Mihail Bogojeski, Michael Gastegger, Mario Geiger, Tess E. Smidt, Klaus-Robert Müller

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Equivariant message passing for the prediction of tensorial properties and molecular spectra.

Kristof Schütt, Oliver T. Unke, Michael Gastegger

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

High-dimensional potential energy surfaces for molecular simulations: from empiricism to machine learning.

Oliver T. Unke, Debasish Koner, Sarbani Patra, Silvan Käser, Markus Meuwly

Mach. Learn. Sci. Technol., 2020

2017

Toolkit for the Construction of Reproducing Kernel-Based Representations of Data: Application to Multidimensional Potential Energy Surfaces.

Oliver T. Unke, Markus Meuwly

J. Chem. Inf. Model., August, 2017

Migration of small ligands in globins: Xe diffusion in truncated hemoglobin N.

Polydefkis Diamantis, Oliver T. Unke, Markus Meuwly

PLoS Comput. Biol., 2017