45 citations · 91 across the 4 of their papers we have counts for
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physics.chem-ph2019★ 22 cited
Resolution limit of data-driven coarse-grained models spanning chemical space
Kiran H. Kanekal, Tristan Bereau
Increasing the efficiency of materials design and discovery remains a significant challenge, especially given the prohibitively large size of chemical compound space. The use of a…
cond-mat.soft2019★ 24 cited
Controlled exploration of chemical space by machine learning of coarse-grained representations
Christian Hoffmann, Roberto Menichetti, Kiran H. Kanekal +1
The size of chemical compound space is too large to be probed exhaustively. This leads high-throughput protocols to drastically subsample and results in sparse and non-uniform data…