MACE: Higher order equivariant message passing neural networks for fast and accurate force fields I Batatia, DP Kovacs, G Simm, C Ortner, G Csányi Advances in Neural Information Processing Systems 35, 11423-11436, 2022 | 279 | 2022 |
Exploration of Reaction Pathways and Chemical Transformation Networks GN Simm, AC Vaucher, M Reiher The Journal of Physical Chemistry A 123 (2), 385-399, 2018 | 199 | 2018 |
Heuristics-Guided Exploration of Reaction Mechanisms M Bergeler, GN Simm, J Proppe, M Reiher Journal of chemical theory and computation 11 (12), 5712-5722, 2015 | 163 | 2015 |
The Harvard organic photovoltaic dataset SA Lopez, EO Pyzer-Knapp, GN Simm, T Lutzow, K Li, LR Seress, ... Scientific Data 3, 160086, 2016 | 124 | 2016 |
Context-Driven Exploration of Complex Chemical Reaction Networks GN Simm, M Reiher Journal of chemical theory and computation 13 (12), 6108-6119, 2017 | 119 | 2017 |
A Generative Model for Molecular Distance Geometry GNC Simm, JM Hernández-Lobato International Conference on Machine Learning, 8949-8958, 2019 | 118 | 2019 |
Reinforcement learning for molecular design guided by quantum mechanics GNC Simm, R Pinsler, JM Hernández-Lobato International Conference on Machine Learning, 8959-8969, 2020 | 112 | 2020 |
A Bayesian approach to calibrating high-throughput virtual screening results and application to organic photovoltaic materials EO Pyzer-Knapp, GN Simm, AA Guzik Materials Horizons 3 (3), 226-233, 2016 | 88 | 2016 |
Error-Controlled Exploration of Chemical Reaction Networks with Gaussian Processes GN Simm, M Reiher Journal of chemical theory and computation 14 (10), 5238-5248, 2018 | 86 | 2018 |
Systematic error estimation for chemical reaction energies GN Simm, M Reiher Journal of chemical theory and computation 12 (6), 2762-2773, 2016 | 83 | 2016 |
The Design Space of E (3)-Equivariant Atom-Centered Interatomic Potentials I Batatia, S Batzner, DP Kovács, A Musaelian, GNC Simm, R Drautz, ... arXiv preprint arXiv:2205.06643, 2022 | 79 | 2022 |
Uncertainty quantification for quantum chemical models of complex reaction networks J Proppe, T Husch, GN Simm, M Reiher Faraday discussions 195, 497-520, 2016 | 77 | 2016 |
Symmetry-Aware Actor-Critic for 3D Molecular Design GNC Simm, R Pinsler, G Csányi, JM Hernández-Lobato arXiv preprint arXiv:2011.12747, 2020 | 65 | 2020 |
Systematic microsolvation approach with a cluster‐continuum scheme and conformational sampling GN Simm, PL Türtscher, M Reiher Journal of Computational Chemistry 41 (12), 1144-1155, 2020 | 63 | 2020 |
DOCKSTRING: easy molecular docking yields better benchmarks for ligand design M García-Ortegón, GNC Simm, AJ Tripp, JM Hernández-Lobato, A Bender, ... Journal of Chemical Information and Modeling, 2021 | 61 | 2021 |
Error assessment of computational models in chemistry GN Simm, J Proppe, M Reiher CHIMIA International Journal for Chemistry 71 (4), 202-208, 2017 | 40 | 2017 |
Flow Annealed Importance Sampling Bootstrap LI Midgley, V Stimper, GNC Simm, B Schölkopf, JM Hernández-Lobato arXiv preprint arXiv:2208.01893, 2022 | 38 | 2022 |
A Fresh Look at De Novo Molecular Design Benchmarks A Tripp, GNC Simm, JM Hernández-Lobato NeurIPS 2021 AI for Science Workshop, 2021 | 14 | 2021 |
Bootstrap Your Flow LI Midgley, V Stimper, GNC Simm, JM Hernández-Lobato arXiv preprint arXiv:2111.11510, 2021 | 4 | 2021 |
qcscine/chemoton: Release 2.2. 0 M Bensberg, SA Grimmel, GN Simm, JG Sobez, M Steiner, P Türtscher, ... Zenodo, 2022 | 3 | 2022 |