About Me
I’m a Research Scientist @ SAIT, Samsung Electronics.
My research interest includes:
- Post-hoc analysis & applications of pre-traiend models (especially, Foundation Models).
- Generalization of deep learning via the lens of loss landscape.
- Bayesian deep learning (especially, Laplace Approximation).
- Explainability and interpretability of large-scale neural networks.
Education
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Ph.D. in Graduate School of AI, Korea Advanced Institute of Science and Technology (KAIST)
Mar. 2019 - Feb. 2024 -
M.S. in Industrial Engineering (Mathematical optimization), Seoul National University (SNU)
Mar. 2017 - Feb. 2019 -
B.S. in Industrial Engineering & Mathematical Science, Seoul National University (SNU)
Mar. 2013 - Feb. 2017
Published Papers
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GEX: A flexible method for approximating influence via Geometric Ensemble
Sung-Yub Kim, Kyungsu Kim, Eunho Yang
NeurIPS, 2023 -
RGE: A Repulsive Graph Rectification for Node Classification via Influence
Jaeyun Song*, Sung-Yub Kim*, Eunho Yang (*: equal contribution)
ICML, 2023 -
Scale-invariant Bayesian Neural Networks with Connectivity Tangent Kernel
Sung-Yub Kim, Sihwan Park, Kyungsu Kim, Eunho Yang
ICLR, 2023 (Spotlighted) -
Generalized Tsallis Entropy Reinforcement Learning and Its Application to Soft Mobile Robots
Kyungjae Lee, Sung-Yub Kim, Sungbin Lim, Sungjoon Choi, Mineui Hong, Jaein Kim, Yong-Lae Park, and Songhwai Oh
Robotics: Science and Systems Foundation
Preprints
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TTD: Text-Tag Self-Distillation Enhancing Image-Text Alignment in CLIP to Alleviate Single Tag Bias
Sanghyun Jo*, Soohyun Ryu*, Sungyub Kim, Eunho Yang, Kyungsu Kim (*: equal contribution) -
Post-Training Recovery from Injected Bias with Self-Influence
Jaeyun Song* and Yeonsung Jung* and June Yong Yang* and Jin-Hwa Kim and Sung-Yub Kim and Eunho Yang (*: equal contribution) -
Bias Decay Matters: Improving Large Batch Optimization with Connectivity Sharpness
Sung-Yub Kim, Sihwan Park, Yong-Deok Kim, Eunho Yang -
Reliable Estimation of Individual Treatment Effect with Causal Information Bottleneck
Sung-Yub Kim, Yongsu Baek, Sung Ju Hwang, Eunho Yang
Projects
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Autonomous Intelligent Digital Companion Framework and Application
Korea Electronics Technology Institute, 2019-2021 -
A study on adaptive point and regional OOD detection techniques based on sub-task generation
Samsung, 2020-2023 -
A machine learning and statistical inference framework for explainable artificial intelligence
Institute of Information & Communications Technology Planning & Evaluation (IITP), 2022-2023 -
A Study on Optimization and Network Interpretation Method for Large-Scale Machine Learning
National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT), 2022-2023