Abstract
Original language | English |
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Article number | 100588 |
Pages (from-to) | 1-27 |
Number of pages | 27 |
Journal | Patterns |
Volume | 3 |
Issue number | 10 |
DOIs | |
Publication status | Published - 14 Oct 2022 |
Bibliographical note
Funding Information:The authors thank Greg Landrum, Daniel Flam-Shepherd, Suliman Sharif, and Bettina Lier for valuable comments on the manuscript. The authors also thank Sara Bebbington of IOP Publishing and Zamyla Chan and Erin Warner of the University of Toronto Acceleration Consortium for helping to organize the SELFIES workshop. M.K. acknowledges support from the FWF (Austrian Science Fund) via the Erwin Schrödinger fellowship no. J4309. R.F.L. received a PhD Scholarship from the São Paulo Research Foundation (FAPESP) – grant #2021/01633-3. This study was financed in part by CAPES – Finance Code 001. R.P. acknowledges funding through a Postdoc.Mobility fellowship by the Swiss National Science Foundation (SNSF; project no. 191127). A.W. would like to thank the Natural Sciences and Engineering Council of Canada (NSERC) for financial support via a CGS-M scholarship. G.T. acknowledges financial support from NSERC via the PGS-D scholarship. R.Y. acknowledges support from the US Department of Energy, Office of Science, AWS Machine Learning Research Award, and NSF grant #2037745. D.L. and G.F.v.R. were supported by the von Lilienfeld lab at the University of Vienna. A.D.W. was supported by the National Institute of General Medical Sciences of the National Institutes of Health under award number R35GM137966. K.M.J. and B.S. acknowledge funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (grant agreement no. 666983, MaGic). J.M.N.-D. acknowledges support by the National Council for Science and Technology (CONACYT) under award number CVU 105568. P.S. acknowledges support from the NCCR Catalysis (grant number 180544), a National Centre of Competence in Research funded by the Swiss National Science Foundation. S.M.M. was supported by the Swiss National Science Foundation (SNSF) under grant P2ELP2_195155. U.S. acknowledges support from the Deutsche Forschungsgemeinschaft (DFG) within NFDI4Chem (grant no. NFDI4-1). Q.A. acknowledges support from the National Science Foundation (grant no. DMR-1928882). A.A.G. acknowledges support from the Canada 150 Research Chairs Program, the Google Focused Award, and Dr. Anders G. Frøseth.
Funding Information:
The authors thank Greg Landrum, Daniel Flam-Shepherd, Suliman Sharif, and Bettina Lier for valuable comments on the manuscript. The authors also thank Sara Bebbington of IOP Publishing and Zamyla Chan and Erin Warner of the University of Toronto Acceleration Consortium for helping to organize the Selfies workshop. M.K. acknowledges support from the FWF (Austrian Science Fund) via the Erwin Schrödinger fellowship no. J4309 . R.F.L. received a PhD Scholarship from the São Paulo Research Foundation (FAPESP) – grant # 2021/01633-3 . This study was financed in part by CAPES – Finance Code 001 . R.P. acknowledges funding through a Postdoc.Mobility fellowship by the Swiss National Science Foundation (SNSF; project no. 191127 ). A.W. would like to thank the Natural Sciences and Engineering Council of Canada (NSERC) for financial support via a CGS-M scholarship. G.T. acknowledges financial support from NSERC via the PGS-D scholarship. R.Y. acknowledges support from the US Department of Energy , Office of Science, AWS Machine Learning Research Award, and NSF grant # 2037745 . D.L. and G.F.v.R. were supported by the von Lilienfeld lab at the University of Vienna . A.D.W. was supported by the National Institute of General Medical Sciences of the National Institutes of Health under award number R35GM137966 . K.M.J. and B.S. acknowledge funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement no. 666983 , MaGic). J.M.N.-D. acknowledges support by the National Council for Science and Technology (CONACYT) under award number CVU 105568 . P.S. acknowledges support from the NCCR Catalysis (grant number 180544 ), a National Centre of Competence in Research funded by the Swiss National Science Foundation . S.M.M. was supported by the Swiss National Science Foundation (SNSF) under grant P2ELP2_195155 . U.S. acknowledges support from the Deutsche Forschungsgemeinschaft (DFG) within NFDI4Chem (grant no. NFDI4-1 ). Q.A. acknowledges support from the National Science Foundation (grant no. DMR-1928882 ). A.A.G. acknowledges support from the Canada 150 Research Chairs Program, the Google Focused Award , and Dr. Anders G. Frøseth.
Publisher Copyright:
© 2022 The Author(s)
Funding
The authors thank Greg Landrum, Daniel Flam-Shepherd, Suliman Sharif, and Bettina Lier for valuable comments on the manuscript. The authors also thank Sara Bebbington of IOP Publishing and Zamyla Chan and Erin Warner of the University of Toronto Acceleration Consortium for helping to organize the SELFIES workshop. M.K. acknowledges support from the FWF (Austrian Science Fund) via the Erwin Schrödinger fellowship no. J4309. R.F.L. received a PhD Scholarship from the São Paulo Research Foundation (FAPESP) – grant #2021/01633-3. This study was financed in part by CAPES – Finance Code 001. R.P. acknowledges funding through a Postdoc.Mobility fellowship by the Swiss National Science Foundation (SNSF; project no. 191127). A.W. would like to thank the Natural Sciences and Engineering Council of Canada (NSERC) for financial support via a CGS-M scholarship. G.T. acknowledges financial support from NSERC via the PGS-D scholarship. R.Y. acknowledges support from the US Department of Energy, Office of Science, AWS Machine Learning Research Award, and NSF grant #2037745. D.L. and G.F.v.R. were supported by the von Lilienfeld lab at the University of Vienna. A.D.W. was supported by the National Institute of General Medical Sciences of the National Institutes of Health under award number R35GM137966. K.M.J. and B.S. acknowledge funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (grant agreement no. 666983, MaGic). J.M.N.-D. acknowledges support by the National Council for Science and Technology (CONACYT) under award number CVU 105568. P.S. acknowledges support from the NCCR Catalysis (grant number 180544), a National Centre of Competence in Research funded by the Swiss National Science Foundation. S.M.M. was supported by the Swiss National Science Foundation (SNSF) under grant P2ELP2_195155. U.S. acknowledges support from the Deutsche Forschungsgemeinschaft (DFG) within NFDI4Chem (grant no. NFDI4-1). Q.A. acknowledges support from the National Science Foundation (grant no. DMR-1928882). A.A.G. acknowledges support from the Canada 150 Research Chairs Program, the Google Focused Award, and Dr. Anders G. Frøseth. The authors thank Greg Landrum, Daniel Flam-Shepherd, Suliman Sharif, and Bettina Lier for valuable comments on the manuscript. The authors also thank Sara Bebbington of IOP Publishing and Zamyla Chan and Erin Warner of the University of Toronto Acceleration Consortium for helping to organize the Selfies workshop. M.K. acknowledges support from the FWF (Austrian Science Fund) via the Erwin Schrödinger fellowship no. J4309 . R.F.L. received a PhD Scholarship from the São Paulo Research Foundation (FAPESP) – grant # 2021/01633-3 . This study was financed in part by CAPES – Finance Code 001 . R.P. acknowledges funding through a Postdoc.Mobility fellowship by the Swiss National Science Foundation (SNSF; project no. 191127 ). A.W. would like to thank the Natural Sciences and Engineering Council of Canada (NSERC) for financial support via a CGS-M scholarship. G.T. acknowledges financial support from NSERC via the PGS-D scholarship. R.Y. acknowledges support from the US Department of Energy , Office of Science, AWS Machine Learning Research Award, and NSF grant # 2037745 . D.L. and G.F.v.R. were supported by the von Lilienfeld lab at the University of Vienna . A.D.W. was supported by the National Institute of General Medical Sciences of the National Institutes of Health under award number R35GM137966 . K.M.J. and B.S. acknowledge funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement no. 666983 , MaGic). J.M.N.-D. acknowledges support by the National Council for Science and Technology (CONACYT) under award number CVU 105568 . P.S. acknowledges support from the NCCR Catalysis (grant number 180544 ), a National Centre of Competence in Research funded by the Swiss National Science Foundation . S.M.M. was supported by the Swiss National Science Foundation (SNSF) under grant P2ELP2_195155 . U.S. acknowledges support from the Deutsche Forschungsgemeinschaft (DFG) within NFDI4Chem (grant no. NFDI4-1 ). Q.A. acknowledges support from the National Science Foundation (grant no. DMR-1928882 ). A.A.G. acknowledges support from the Canada 150 Research Chairs Program, the Google Focused Award , and Dr. Anders G. Frøseth.
Funders | Funder number |
---|---|
Canada 150 Research Chairs Program | |
NCCR Catalysis | 180544 |
National Science Foundation | DMR-1928882, 2037745 |
National Science Foundation | |
National Institutes of Health | R35GM137966 |
National Institutes of Health | |
U.S. Department of Energy | |
National Institute of General Medical Sciences | |
Office of Science | |
Amazon Web Services | |
Horizon 2020 Framework Programme | |
Natural Sciences and Engineering Research Council of Canada | |
European Research Council | |
Deutsche Forschungsgemeinschaft | NFDI4-1 |
Deutsche Forschungsgemeinschaft | |
Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung | 191127 |
Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung | |
Fundação de Amparo à Pesquisa do Estado de São Paulo | 2021/01633-3 |
Fundação de Amparo à Pesquisa do Estado de São Paulo | |
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior | |
Austrian Science Fund | J4309 |
Austrian Science Fund | |
Universität Wien | |
Consejo Nacional de Ciencia y Tecnología | CVU 105568 |
Consejo Nacional de Ciencia y Tecnología | |
Horizon 2020 | 666983 |
Horizon 2020 | |
National Centre of Competence in Research Robotics | P2ELP2_195155 |
National Centre of Competence in Research Robotics |
Keywords
- DSML 3: Development/pre-production: Data science output has been rolled out/validated across multiple domains/problems