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Neural networks and kernel ridge regression for excited states dynamics of CH2NH$_2^+$: From single-state to multi-state representations and multi-property machine learning models., , , , and . Mach. Learn. Sci. Technol., 1 (2): 25009 (2020)Photoluminescence and Conductivity of Self-Assembled π–π Stacks of Perylene Bisimide Dyes, , , , , , , , and . Chemistry – A European Journal, 13 (2): 436--449 (2007)Local control theory applied to molecular photoassociation, and . The Journal of Chemical Physics, 127 (8): 084115 (August 2007)On the divergence of time-dependent perturbation theory applied to laser-induced molecular transitions, , and . Journal of Physics B: Atomic, Molecular and Optical Physics, 42 (19): 195402 (2009)Classical aspects emerging from local control of energy and particle transfer in molecules, , and . Journal of Photochemistry and Photobiology A: Chemistry, 180 (3): 271 - 276 (2006)Coherent Control of Photochemical and Photobiological Processes.Molecular dump processes induced by chirped laser pulses, , , and . The Journal of Chemical Physics, 129 (7): 074303 (August 2008)Solving the electronic Schrödinger equation for multiple nuclear geometries with weight-sharing deep neural networks., , , , and . CoRR, (2021)Predissociation and dissociation dynamics in quantum control fields, and . Chemical Physics Letters, 407 (4): 471 - 476 (2005)Machine learning and excited-state molecular dynamics., and . Mach. Learn. Sci. Technol., 1 (4): 43001 (2020)Gold-standard solutions to the Schrödinger equation using deep learning: How much physics do we need?, , , and . NeurIPS, (2022)