Showing 21–40 of 46 results
/ Date/ Name
Feb 2, 2021Analyzing dynamical disorder for charge transport in organic semiconductors via machine learningJun 20, 2023JARVIS-Leaderboard: A Large Scale Benchmark of Materials Design MethodsAug 1, 2025Learning Potential Energy Surfaces of Hydrogen Atom Transfer Reactions in PeptidesMar 21, 2023Neural networks trained on synthetically generated crystals can extract structural information from ICSD powder X-ray diffractogramsMar 15, 2023Accurate GW frontier orbital energies of 134 kilo moleculesAug 5, 2022Graph neural networks for materials science and chemistryFeb 5, 2025Symmetry-Aware Bayesian Flow Networks for Crystal GenerationMar 31, 2022SELFIES and the future of molecular string representationsJun 20, 2025Predicting New Research Directions in Materials Science using Large Language Models and Concept GraphsDec 17, 2025Multi-stage Bayesian optimisation for dynamic decision-making in self-driving labsFeb 3, 2026Efficient Training of Boltzmann Generators Using Off-Policy Log-Dispersion RegularizationDec 2, 2025Towards a fully differentiable digital twin for solar cellsApr 30, 2026Hyper-Dimensional Fingerprints as Molecular RepresentationsMay 25, 2023Quantifying the Intrinsic Usefulness of Attributional Explanations for Graph Neural Networks with Artificial Simulatability StudiesApr 25, 2024Global Concept Explanations for Graphs by Contrastive LearningApr 21, 2023What is missing in autonomous discovery: Open challenges for the communityApr 3, 2025Improving Counterfactual Truthfulness for Molecular Property Prediction through Uncertainty QuantificationFeb 24, 2020Neural Message Passing on High Order PathsMar 7, 2022Charge Transfer Simulations using Hamiltonian Elements and Forces from Neural NetworksApr 4, 2022On scientific understanding with artificial intelligence