Machine learning of free energies in chemical compound space using ensemble representations: Reaching experimental uncertainty for solvation J Weinreich, NJ Browning, OA von Lilienfeld The Journal of Chemical Physics 154 (13), 134113, 2021 | 49 | 2021 |
Properties of α-Brass nanoparticles. 1. Neural network potential energy surface J Weinreich, A Römer, ML Paleico, J Behler The Journal of Physical Chemistry C 124 (23), 12682-12695, 2020 | 30 | 2020 |
Properties of α-Brass Nanoparticles II: Structure and Composition J Weinreich, ML Paleico, J Behler The Journal of Physical Chemistry C 125 (27), 14897-14909, 2021 | 12 | 2021 |
Ab initio machine learning of phase space averages J Weinreich, D Lemm, GF von Rudorff, OA von Lilienfeld The Journal of Chemical Physics 157 (2), 024303, 2022 | 9 | 2022 |
Boltzmann Generators and the New Frontier of Computational Sampling in Many-Body Systems A Coretti, S Falkner, J Weinreich, C Dellago, OA von Lilienfeld arXiv preprint arXiv:2404.16566, 2024 | 1 | 2024 |
Evolutionary Monte Carlo of QM properties in chemical space: Electrolyte design K Karandashev, J Weinreich, S Heinen, DJ Arismendi Arrieta, ... Journal of Chemical Theory and Computation, 2023 | 1 | 2023 |
Encrypted machine learning of molecular quantum properties J Weinreich, GF von Rudorff, OA von Lilienfeld Machine Learning: Science and Technology 4 (2), 025017, 2023 | 1 | 2023 |
Cost-Informed Bayesian Reaction Optimization A Schoepfer, J Weinreich, R Laplaza, J Waser, C Corminboeuf | | 2024 |
Learning on Compressed Molecular Representations J Weinreich, D Probst | | 2024 |
Parameter-Free Molecular Classification and Regression with Gzip J Weinreich, D Probst | | 2023 |
Understanding Representations by Exploring Galaxies in Chemical Space J Weinreich, K Karandashev, GF von Rudorff arXiv preprint arXiv:2309.09194, 2023 | | 2023 |
Thesis: Enhancing the accuracy and privacy of machine learning predictions for molecular ensemble properties J Weinreich https://utheses.univie.ac.at/detail/66535/, 2023 | | 2023 |