Title
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Energy-Based Coarse-Graining in Molecular Dynamics: A Flow-Based Framework without DataJournal of Chemical Theory and Computation (JCTC), 2025 Maximilian Stupp P. S. Koutsourelakis 279 1 0 29 Apr 2025
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Learning Macroscopic Dynamics from Partial Microscopic ObservationsNeural Information Processing Systems (NeurIPS), 2024 Mengyi Chen Qianxiao Li AI4CE 275 1 0 31 Oct 2024
EquiJump: Protein Dynamics Simulation via SO(3)-Equivariant Stochastic Interpolants Allan dos Santos Costa Ilan Mitnikov Franco Pellegrini Ameya Daigavane Mario Geiger Zhonglin Cao Karsten Kreis Tess E. Smidt E. Küçükbenli J. Jacobson 181 8 0 12 Oct 2024
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Foundation Inference Models for Markov Jump ProcessesNeural Information Processing Systems (NeurIPS), 2024 David Berghaus K. Cvejoski Patrick Seifner C. Ojeda Ramses J. Sanchez 275 8 0 10 Jun 2024
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Probabilistic Graph Rewiring via Virtual Nodes Chendi Qian Andrei Manolache Christopher Morris Mathias Niepert AI4CE 273 11 0 27 May 2024
Conditional Normalizing Flows for Active Learning of Coarse-Grained Molecular Representations Henrik Schopmans Pascal Friederich AI4CE 306 5 0 02 Feb 2024
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DiAMoNDBack: Diffusion-denoising Autoregressive Model for Non-Deterministic Backmapping of Cα Protein TracesJournal of Chemical Theory and Computation (JCTC), 2023 Michael S. Jones Kirill Shmilovich Andrew L. Ferguson DiffM 186 23 0 23 Jul 2023
CoarsenConf: Equivariant Coarsening with Aggregated Attention for Molecular Conformer GenerationJournal of Chemical Information and Modeling (JCIM), 2023 Danny Reidenbach Aditi S. Krishnapriyan 171 9 0 26 Jun 2023
Top-down machine learning of coarse-grained protein force-fieldsJournal of Chemical Theory and Computation (JCTC), 2023 Carles Navarro Maciej Majewski Gianni De Fabritiis AI4CE 283 16 0 20 Jun 2023
Implicit Transfer Operator Learning: Multiple Time-Resolution Surrogates for Molecular Dynamics Mathias Jacob Schreiner Ole Winther Simon Olsson OOD AI4CE 299 20 0 29 May 2023
On the Relationships between Graph Neural Networks for the Simulation of Physical Systems and Classical Numerical Methods Artur Toshev Ludger Paehler A. Panizza Nikolaus A. Adams AI4CE PINN 236 5 0 31 Mar 2023
FlexVDW: A machine learning approach to account for protein flexibility in ligand docking Patricia Suriana Joseph M. Paggi R. Dror AI4CE 71 2 0 20 Mar 2023
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EPR-Net: Constructing non-equilibrium potential landscape via a variational force projection formulationNational Science Review (NSR), 2023 Yue Zhao Wei Zhang Tiejun Li DiffM 132 10 0 05 Jan 2023
Scalable Bayesian Uncertainty Quantification for Neural Network Potentials: Promise and PitfallsJournal of Chemical Theory and Computation (JCTC), 2022 Stephan Thaler Gregor Doehner Julija Zavadlav 229 23 0 15 Dec 2022
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Investigation of Machine Learning-based Coarse-Grained Mapping Schemes for Organic MoleculesHellenic Conference on Artificial Intelligence (HAI), 2022 Dimitris Nasikas E. Ricci Georgios Paliouras V. Karkaletsis D. Theodorou Niki Vergadou 126 7 0 26 Sep 2022
Graph neural networks for materials science and chemistryCommunications Materials (Commun. Mater.), 2022 Patrick Reiser Marlen Neubert André Eberhard Luca Torresi Chen Zhou ... Houssam Metni Clint van Hoesel Henrik Schopmans T. Sommer Pascal Friederich GNN AI4CE 268 567 0 05 Aug 2022
Contrastive Learning of Coarse-Grained Force FieldsJournal of Chemical Theory and Computation (JCTC), 2022 Xinqiang Ding Bin W. Zhang 126 25 0 22 May 2022
Simulate Time-integrated Coarse-grained Molecular Dynamics with Multi-Scale Graph Networks Xiang Fu T. Xie Nathan J. Rebello B. Olsen Tommi Jaakkola AI4CE 231 25 0 21 Apr 2022
Automatic Identification of Chemical MoietiesPhysical Chemistry, Chemical Physics - PCCP (PCCP), 2022 Jonas Lederer M. Gastegger Kristof T. Schütt Michael C. Kampffmeyer Klaus-Robert Muller Oliver T. Unke 145 5 0 30 Mar 2022
TorchMD-NET: Equivariant Transformers for Neural Network based Molecular Potentials Philipp Thölke Gianni De Fabritiis AI4CE 327 239 0 05 Feb 2022
Generative Coarse-Graining of Molecular ConformationsInternational Conference on Machine Learning (ICML), 2022 Wujie Wang Minkai Xu Chen Cai Benjamin Kurt Miller Tess E. Smidt Yusu Wang Jian Tang Rafael Gómez-Bombarelli 125 43 0 28 Jan 2022
GraphVAMPNet, using graph neural networks and variational approach to markov processes for dynamical modeling of biomolecules Mahdi Ghorbani Samarjeet Prasad Jeffery B. Klauda B. Brooks GNN 92 37 0 12 Jan 2022
Graph Neural Networks Accelerated Molecular DynamicsJournal of Chemical Physics (JCP), 2021 Zijie Li Kazem Meidani Prakarsh Yadav A. Farimani GNN AI4CE 180 70 0 06 Dec 2021
Smooth Normalizing Flows Jonas Köhler Andreas Krämer Frank Noé 244 62 0 01 Oct 2021
Learning neural network potentials from experimental data via Differentiable Trajectory ReweightingNature Communications (Nat Commun), 2021 Stephan Thaler Julija Zavadlav 202 84 0 02 Jun 2021
TorchMD: A deep learning framework for molecular simulationsJournal of Chemical Theory and Computation (JCTC), 2020 Stefan Doerr Maciej Majewski Adria Pérez Andreas Krämer C. Clementi Frank Noe T. Giorgino Gianni De Fabritiis AI4CE 271 192 0 22 Dec 2020
Artificial intelligence techniques for integrative structural biology of intrinsically disordered proteinsCurrent Opinion in Structural Biology (COSB), 2020 A. Ramanathan Henglong Ma Akash Parvatikar C. Chennubhotla AI4CE 147 44 0 01 Dec 2020
Relevance of Rotationally Equivariant Convolutions for Predicting Molecular Properties Benjamin Kurt Miller Mario Geiger Tess E. Smidt Frank Noé 276 80 0 19 Aug 2020