Synergies Between Quantum Mechanics and Machine Learning in Reaction Prediction
By Peter Sadowski, David Fooshee, Niranjan A. Subrahmanya, Pierre Baldi. 2016
61 citations recorded by the source corpus.
Subfields: Computational Theory and Mathematics, Materials Chemistry, Physical and Theoretical Chemistry
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In Computational Theory and Mathematics
In Materials Chemistry
In Physical and Theoretical Chemistry
Citations in the corpus
- Deep Learning for Deep Chemistry: Optimizing the Prediction of Chemical Patterns (2019, unknown): “…al., 2013, 2015; Montavon et al., 2013; Schütt et al., 2014; Alipanahi et al., 2015; Botu and Ramprasad, 2015b; De et al., 2016; Faber et al., 2016; Sadowski et al., 2016; Wei et al., 2016; Brockherde et al., 2017; Chmiela et al., 2017, 2018; Smith et al., 2017; Wu et al., 2017; Gómez-Bombarelli…”
- Integrating Scientific Knowledge with Machine Learning for Engineering and Environmental Systems (2020, background): “1) [266] [10] [219] [158] [140] [182] [203] [76] [86] [130] [174] [204] [231] [313] [121] [125] [187] [92] [306] [180] [298] [184] [267] [39] [247] [133] [130] [231] [298] [173] [66] [24] [255] [12] [17] [203] [204] [213] [239] [125] [281] [214] [176] [249] [310] [309] [311] [245] [78] [266] [297] [”
- Integrating Physics-Based Modeling with Machine Learning: A Survey (2020, background): “…earth systems [214], climate science [75, 135, 186], turbulence modeling [28, 179, 273], material discovery [40, 202, 226], quantum chemistry [222, 228], biological sciences [285], and hydrology [275]), and it is being performed in the context of diverse objectives specific to these…”