Yongchan Kwon

Bayesian's eye on molecular science: Bayesian deep optimization of Onsager-Machlup action learning for uncertainty quantification and active learning of molecular properties

Seongok Ryu, Yongchan Kwon, Sang-Yeon Hwang, 2019 .

Principled Learning Method for Wasserstein distributionally robust optimization with local perturbations

Joong-Ho Won, Yongchan Kwon, Myunghee Cho Paik, 2020, ICML.

Estimation of Hand Motion from Piezoelectric Soft Sensor Using Deep Recurrent Network

Yongchan Kwon, KangGeon Kim, Sung Hee Kim, 2020, Applied Sciences.

An analytic formulation for positive-unlabeled learning via weighted integral probability metric.

Masashi Sugiyama, Yongchan Kwon, Myunghee Cho Paik, 2019 .

Competing AI: How does competition feedback affect machine learning?

Yongchan Kwon, James Zou, Antonio Ginart, 2020, AISTATS.

Efficient computation and analysis of distributional Shapley values pdf

Yongchan Kwon, James Zou, Manuel A. Rivas, 2020, ArXiv.

Lipschitz Continuous Autoencoders in Application to Anomaly Detection

Yongchan Kwon, Young-geun Kim, Myunghee Cho Paik, 2020, AISTATS.