123 citations · 876 across the 50 of their papers we have counts for
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stat.ML2021★ 1 cited
Robustness and Reliability When Training With Noisy Labels
Amanda Olmin, Fredrik Lindsten
Labelling of data for supervised learning can be costly and time-consuming and the risk of incorporating label noise in large data sets is imminent. When training a flexible discri…
cond-mat.mtrl-sci2021
Graph-based machine learning beyond stable materials and relaxed crystal structures
Filip Ekström, Rickard Armiento, Fredrik Lindsten
There has been a recent surge of interest in using machine learning to approximate density functional theory (DFT) in materials science. However, many of the most performant models…