19 citations · 19 across the 3 of their papers we have counts for
3 papers
cs.LG2022
Scale-invariant Bayesian Neural Networks with Connectivity Tangent Kernel
SungYub Kim, Sihwan Park, Kyungsu Kim +1
Explaining generalizations and preventing over-confident predictions are central goals of studies on the loss landscape of neural networks. Flatness, defined as loss invariability…
cs.LG2019
Reliable Estimation of Individual Treatment Effect with Causal Information Bottleneck
Sungyub Kim, Yongsu Baek, Sung Ju Hwang +1
Estimating individual level treatment effects (ITE) from observational data is a challenging and important area in causal machine learning and is commonly considered in diverse mis…
cs.LG2019★ 19 cited
Tsallis Reinforcement Learning: A Unified Framework for Maximum Entropy Reinforcement Learning
Kyungjae Lee, Sungyub Kim, Sungbin Lim +2
In this paper, we present a new class of Markov decision processes (MDPs), called Tsallis MDPs, with Tsallis entropy maximization, which generalizes existing maximum entropy reinfo…