Showing 1–20 of 21 results
/ Date/ Name
Mar 23, 2026Characterizing High-Capacity Janus Aminobenzene-Graphene Anode for Sodium-Ion Batteries with Machine LearningSep 18, 2019Construction of Machine Learned Force Fields with Quantum Chemical Accuracy: Applications and Chemical InsightsJun 8, 2021BIGDML: Towards Exact Machine Learning Force Fields for MaterialsJan 10, 2021On the forbidden graphene's ZO (out-of-plane optic) phononic band-analog vibrational modes in fullerenesMar 7, 2025Machine Learned Force Fields: Fundamentals, its reach, and challengesNov 1, 2025Delta-learned force fields for nonbonded interactions: Addressing the strength mismatch between covalent-nonbonded interaction for global modelsJan 2, 2022Super-resolution in Molecular Dynamics Trajectory Reconstruction with Bi-Directional Neural NetworksAug 10, 2020Molecular Force Fields with Gradient-Domain Machine Learning (GDML): Comparison and Synergies with Classical Force FieldsJan 19, 2019Molecular Force Fields with Gradient-Domain Machine Learning: Construction and Application to Dynamics of Small Molecules with Coupled Cluster ForcesJun 18, 2020Dynamical Strengthening of Covalent and Non-Covalent Molecular Interactions by Nuclear Quantum Effects at Finite TemperatureApr 29, 2026Towards Accelerated SCF Workflows with Equivariant Density-Matrix Learning and Analytic RefinementNov 15, 2016Machine Learning of Accurate Energy-Conserving Molecular Force FieldsFeb 26, 2018Towards Exact Molecular Dynamics Simulations with Machine-Learned Force FieldsSep 29, 2022Accurate global machine learning force fields for molecules with hundreds of atomsSep 8, 2023Intercavity polariton slows down dynamics in strongly coupled cavitiesDec 17, 2017SchNet - a deep learning architecture for molecules and materialsDec 13, 2019Accurate Molecular Dynamics Enabled by Efficient Physically-Constrained Machine Learning ApproachesMay 1, 2021SpookyNet: Learning Force Fields with Electronic Degrees of Freedom and Nonlocal EffectsOct 14, 2020Machine Learning Force FieldsJun 26, 2017SchNet: A continuous-filter convolutional neural network for modeling quantum interactions