Publications (29)
Deep Reinforcement Learning for De-Novo Drug Design
Mariya Popova, Olexandr Isayev, Alexander Tropsha
CLORE: Content-Level Optimization for Reasoning Efficiency
Yuyang Wu, Qiyao Xue, Guanxing Lu +4
ANI-1: An extensible neural network potential with DFT accuracy at force field computational cost
Justin S. Smith, Olexandr Isayev, Adrian E. Roitberg
A practical guide to machine learning interatomic potentials -- Status and future
Ryan Jacobs, Dane Morgan, Siamak Attarian +27
GEOM-Drugs Revisited: Toward More Chemically Accurate Benchmarks for 3D Molecule Generation
Filipp Nikitin, Ian Dunn, David Ryan Koes +1
Impressive computational acceleration by using machine learning for 2-dimensional super-lubricant materials discovery
Marco Fronzi, Mutaz Abu Ghazaleh, Olexandr Isayev +3
ANI-1: A data set of 20M off-equilibrium DFT calculations for organic molecules
Justin S. Smith, Olexandr Isayev, Adrian E. Roitberg
Machine Learned Hückel Theory: Interfacing Physics and Deep Neural Networks
Tetiana Zubatyuk, Ben Nebgen, Nicholas Lubbers +7
Universal Fragment Descriptors for Predicting Electronic Properties of Inorganic Crystals
Olexandr Isayev, Corey Oses, Cormac Toher +3
Less is more: sampling chemical space with active learning
Justin S. Smith, Ben Nebgen, Nicholas Lubbers +2
Kolmogorov-Arnold Networks in Thermoelectric Materials Design
Marco Fronzi, Michael J. Ford, Kamal Singh Nayal +2
KARA: Efficient Reasoning LLM Serving via Sliding-Window KV Cache Compression
Shen Han, Yuyang Wu, Junpu Yu +1
Simulation Intelligence: Towards a New Generation of Scientific Methods
Alexander Lavin, David Krakauer, Hector Zenil +21
MLatom 3: Platform for machine learning-enhanced computational chemistry simulations and workflows
Pavlo O. Dral, Fuchun Ge, Yi-Fan Hou +15
MolecularRNN: Generating realistic molecular graphs with optimized properties
Mariya Popova, Mykhailo Shvets, Junier Oliva +1
The AFLOW Fleet for Materials Discovery
Cormac Toher, Corey Oses, David Hicks +48
Anticipating the Selectivity of Intramolecular Cyclization Reaction Pathways with Neural Network Potentials
Nicholas Casetti, Dylan Anstine, Olexandr Isayev +1
Applications of Modular Co-Design for De Novo 3D Molecule Generation
Danny Reidenbach, Filipp Nikitin, Olexandr Isayev +1
Transferable Molecular Charge Assignment Using Deep Neural Networks
Ben Nebgen, Nick Lubbers, Justin S. Smith +6
MolErr2Fix: Benchmarking LLM Trustworthiness in Chemistry via Modular Error Detection, Localization, Explanation, and Revision
Yuyang Wu, Jinhui Ye, Shuhao Zhang +3
The Future of Artificial Intelligence and the Mathematical and Physical Sciences (AI+MPS)
Andrew Ferguson, Marisa LaFleur, Lars Ruthotto +97
Structure Prediction of Epitaxial Organic Interfaces with Ogre, Demonstrated for TCNQ on TTF
Saeed Moayedpour, Imaneul Bier, Wen Wen +3
Knowing when to trust machine-learned interatomic potentials
Shams Mehdi, Ilkwon Cho, Olexandr Isayev
AFLOW-ML: A RESTful API for machine-learning predictions of materials properties
Eric Gossett, Cormac Toher, Corey Oses +8
Materials Cartography: Representing and Mining Material Space Using Structural and Electronic Fingerprints
Olexandr Isayev, Denis Fourches, Eugene N. Muratov +4
Scalable Hybrid Deep Neural Networks/Polarizable Potentials Biomolecular Simulations including long-range effects
Théo Jaffrelot Inizan, Thomas Plé, Olivier Adjoua +5
Learning Over Molecular Conformer Ensembles: Datasets and Benchmarks
Yanqiao Zhu, Jeehyun Hwang, Keir Adams +10
Can Agents Price a Reaction? Evaluating LLMs on Chemical Cost Reasoning
Yuyang Wu, Yue Huang, Shuaike Shen +8
MolecularCanvas: LLM-assisted Small-Molecule Drug Discovery via Structure-Guided Constraints
Haoyu Dong, Rui Sheng, Shuhao Zhang +7