74 citations · 76 across the 3 of their papers we have counts for
Showing 2020 · cond-mat.mtrl-sciShow all
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cond-mat.mtrl-sci2020
Predicting and interpreting oxide glass properties by machine learning using large datasets
Daniel R. Cassar, Saulo Martiello Mastelini, Tiago Botari +3
With the advent of powerful computer simulation techniques, it is time to move from the widely used knowledge-guided empirical methods to approaches driven by data science, mainly…
cond-mat.mtrl-sci2020
Designing optical glasses by machine learning coupled with a genetic algorithm
Daniel R. Cassar, Gisele G. dos Santos, Edgar D. Zanotto
Engineering new glass compositions have experienced a sturdy tendency to move forward from (educated) trial-and-error to data- and simulation-driven strategies. In this work, we de…