TY - CHAP
T1 - Learning Representations of Molecules and Materials with Atomistic Neural Networks
AU - Schütt, Kristof T.
AU - Tkatchenko, Alexandre
AU - Müller, Klaus Robert
N1 - Funding Information:
The authors thank Michael Gastegger for valuable discussions and feedback. This work was supported by the Federal Ministry of Education and Research (BMBF) for the Berlin Big Data Center BBDC (01IS14013A) and the Berlin Center for Machine Learning (01IS18037A). Additional support was provided by the Institute for Information & Communications Technology Promotion and funded by the Korean government (MSIT) (No. 2017-0-00451, No. 2017-0-01779). A.T. acknowledges support from the European Research Council (ERC-CoG grant BeStMo).
Publisher Copyright:
© 2020, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.
PY - 2020
Y1 - 2020
N2 - Deep learning has been shown to learn efficient representations for structured data such as images, text, or audio. In this chapter, we present neural network architectures that are able to learn efficient representations of molecules and materials. In particular, the continuous-filter convolutional network SchNet accurately predicts chemical properties across compositional and configurational space on a variety of datasets. Beyond that, we analyze the obtained representations to find evidence that their spatial and chemical properties agree with chemical intuition.
AB - Deep learning has been shown to learn efficient representations for structured data such as images, text, or audio. In this chapter, we present neural network architectures that are able to learn efficient representations of molecules and materials. In particular, the continuous-filter convolutional network SchNet accurately predicts chemical properties across compositional and configurational space on a variety of datasets. Beyond that, we analyze the obtained representations to find evidence that their spatial and chemical properties agree with chemical intuition.
UR - http://www.scopus.com/inward/record.url?scp=85086083702&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-40245-7_11
DO - 10.1007/978-3-030-40245-7_11
M3 - Chapter
AN - SCOPUS:85086083702
T3 - Lecture Notes in Physics
SP - 215
EP - 230
BT - Lecture Notes in Physics
PB - Springer
ER -