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Jan Weinreich
Jan Weinreich
Bestätigte E-Mail-Adresse bei epfl.ch
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Zitiert von
Zitiert von
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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
542021
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
342020
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
152021
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
112022
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
42024
Cost-informed Bayesian reaction optimization
AA Schoepfer, J Weinreich, R Laplaza, J Waser, C Corminboeuf
Digital Discovery 3 (11), 2289-2297, 2024
22024
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
22023
Parameter-Free Molecular Classification and Regression with Gzip
J Weinreich, D Probst
12023
Encrypted machine learning of molecular quantum properties
J Weinreich, GF von Rudorff, OA von Lilienfeld
Machine Learning: Science and Technology 4 (2), 025017, 2023
12023
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry
Y Zimmermann, A Bazgir, Z Afzal, F Agbere, Q Ai, N Alampara, ...
arXiv preprint arXiv:2411.15221, 2024
2024
Calculated state-of-the art results for solvation and ionization energies of thousands of organic molecules relevant to battery design
J Weinreich, K Karandashev, DJA Arrieta, K Hermansson, ...
arXiv preprint arXiv:2411.00994, 2024
2024
Integer linear programming for unsupervised training set selection in molecular machine learning
M Haeberle, P van Gerwen, R Laplaza, KR Briling, J Weinreich, ...
arXiv preprint arXiv:2410.16122, 2024
2024
Learning on Compressed Molecular Representations
J Weinreich, D Probst
2024
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
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