100 citations · 192 across the 13 of their papers we have counts for
3 papers · 1 filter
Uncertainty quantification of molecular property prediction using Bayesian neural network models
Seongok Ryu, Yongchan Kwon, Woo Youn Kim
In chemistry, deep neural network models have been increasingly utilized in a variety of applications such as molecular property predictions, novel molecule designs, and planning c…
Uncertainty quantification of molecular property prediction with Bayesian neural networks
Seongok Ryu, Yongchan Kwon, Woo Youn Kim
Deep neural networks have outperformed existing machine learning models in various molecular applications. In practical applications, it is still difficult to make confident decisi…
Principled analytic classifier for positive-unlabeled learning via weighted integral probability metric
Yongchan Kwon, Wonyoung Kim, Masashi Sugiyama +1
We consider the problem of learning a binary classifier from only positive and unlabeled observations (called PU learning). Recent studies in PU learning have shown superior perfor…