@InProceedings{schiex:LIPIcs.CP.2023.4,
author = {Schiex, Thomas},
title = {{Coupling CP with Deep Learning for Molecular Design and SARS-CoV2 Variants Exploration}},
booktitle = {29th International Conference on Principles and Practice of Constraint Programming (CP 2023)},
pages = {4:1--4:3},
series = {Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN = {978-3-95977-300-3},
ISSN = {1868-8969},
year = {2023},
volume = {280},
editor = {Yap, Roland H. C.},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CP.2023.4},
URN = {urn:nbn:de:0030-drops-190415},
doi = {10.4230/LIPIcs.CP.2023.4},
annote = {Keywords: graphical models, deep learning, constraint programming, cost function networks, random Markov fields, decision-focused learning, protein design}
}