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Molecular machine learning with conformer ensembles., and . CoRR, (2020)Accelerating the screening of amorphous polymer electrolytes by learning to reduce random and systematic errors in molecular dynamics simulations., , , , , , , , , and 1 other author(s). CoRR, (2021)Thermal half-lives of azobenzene derivatives: virtual screening based on intersystem crossing using a machine learning potential., , and . CoRR, (2022)Energy-aware neural architecture selection and hyperparameter optimization., , , , , , , and . IPDPS Workshops, page 732-741. IEEE, (2022)Interpolation and differentiation of alchemical degrees of freedom in machine learning interatomic potentials., and . CoRR, (2024)Generative Models for Automatic Chemical Design., and . CoRR, (2019)Reusability report: Designing organic photoelectronic molecules with descriptor conditional recurrent neural networks., , and . Nat. Mach. Intell., 2 (12): 749-752 (2020)Excited state, non-adiabatic dynamics of large photoswitchable molecules using a chemically transferable machine learning potential., , and . CoRR, (2021)Machine-learning-accelerated simulations enable heuristic-free surface reconstruction., , , , , , and . CoRR, (2023)Molecular machine learning with conformer ensembles., and . Mach. Learn. Sci. Technol., 4 (3): 35025 (September 2023)