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of 3
pro vyhledávání: '"Urbonas, Marius"'
Publikováno v:
The NeurIPS 2023 Workshop on New Frontiers of AI for Drug Discovery and Development (AI4D3 2023), New Orleans, LA, USA, 2023
Designing reward functions that guide generative molecular design (GMD) algorithms to desirable areas of chemical space is of critical importance in AI-driven drug discovery. Traditionally, this has been a manual and error-prone task; the selection o
Externí odkaz:
http://arxiv.org/abs/2312.09865
Autor:
Šileikienė, Virginija1,2 virginija.sileikiene@santa.lt, Urbonas, Marius3, Matačiūnas, Mindaugas3, Norkūnienė, Jolita4
Publikováno v:
Acta Medica Lituanica. 2017, Vol. 24 Issue 4, p209-218. 10p. 1 Color Photograph, 3 Charts.
Publikováno v:
Urbonas, M, Bundy, A, Casanova, J & Li, X 2020, The Use of Max-Sat for Optimal Choice of Automated Theory Repairs . in M Bramer & R Ellis (eds), Artificial Intelligence XXXVII (SGAI 2020) . Lecture Notes in Computer Science, vol. 12498, Lecture Notes in Artificial Intelligence, vol. 12498, pp. 49-63, Fortieth SGAI International Conference on Artificial Intelligence, Cambridge, United Kingdom, 8/12/20 . https://doi.org/10.1007/978-3-030-63799-6_4
The ABC system repairs faulty Datalog theories using a combination of abduction, belief revision and conceptual change via reformation. Abduction and Belief Revision add/delete axioms or delete/add preconditions to rules, respectively. Reformation re
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______3094::1373163140df79c1a26cf9c3036d8ea7
https://www.pure.ed.ac.uk/ws/files/172715207/AI_2020_Max_Sat_Tech_Report_Long_Version.pdf
https://www.pure.ed.ac.uk/ws/files/172715207/AI_2020_Max_Sat_Tech_Report_Long_Version.pdf