Prof. Hyungi Lee - Kookmin University AI·SW Graduate School

Research Overview 연구 개요

Research focuses on Bayesian Neural Networks, stochastic processes in machine learning, Neural Tangent Kernel, Transfer Learning, and uncertainty calibration of Large Language Models.

베이지안 신경망, 기계학습에서의 확률 과정, 뉴럴 탄젠트 커널, 전이 학습, 대규모 언어 모델의 불확실성 보정에 관한 연구를 수행합니다.

Research Areas 연구 분야

Bayesian Neural Networks
Stochastic Processes in ML
Neural Tangent Kernel
Transfer Learning
LLM Uncertainty Calibration

베이지안 신경망
기계학습 확률 과정
뉴럴 탄젠트 커널
전이 학습
LLM 불확실성 보정

Major Achievements 주요 연구 성과

PANGEA: Projection-based augmentation for domain adaptation in LLMs (NeurIPS 2025)
4 papers at NeurIPS 2025, 3 papers at ICLR 2025

Recent Publications 주요 논문

S. Lee, G. Nam, M. Choi, H. Lee, and J. Lee, "PANGEA: Projection-Based Augmentation with Non-Relevant General Data for Enhanced Domain Adaptation in LLMs," NeurIPS, 2025
H. Lee, M. Choi, H. Kim, K. Cho, R. Ranganath, and J. Lee, "Test Time Scaling for Neural Processes," NeurIPS, 2025
C. Jang, D. Cho, S. Lee, H. Lee, and J. Lee, "Reliable Decision-Making via Calibration-Oriented Retrieval-Augmented Generation," NeurIPS, 2025
Y. Jung, H. Lee, W. Chen, T. Mollenhoff, Y. Li, J. Lee, and M. E. Khan, "Compact Memory for Continual Logistic Regression," NeurIPS, 2025
H. Lee, C. Jang, D. B. Lee, and J. Lee, "Dimension Agnostic Neural Processes," ICLR, 2025
H. Lee, S. Lee, and J. Lee, "Variational Bayesian Pseudo-Coreset," ICLR, 2025
B. Park, H. Lee, and J. Lee, "Amortized Control of Continuous State Space Feynman-Kac Model for Irregular Time Series," ICLR, 2025
C. Jang, H. Lee, J. Kim, and J. Lee, "Model Fusion through Bayesian Optimization in Language Model Fine-Tuning," NeurIPS (Spotlight), 2024
H. Lee, G. Nam, E. Fong, and J. Lee, "Enhancing Transfer Learning with Flexible Nonparametric Posterior Sampling," ICLR, 2024
M. Choi, H. Lee, G. Nam, and J. Lee, "Sparse Weight Averaging with Multiple Particles for Iterative Magnitude Pruning," ICLR, 2024
B. Kim, H. Lee, and J. Lee, "Function Space Bayesian Pseudocoreset for Bayesian Neural Networks," NeurIPS, 2023
E. Yun, H. Lee, G. Nam, and J. Lee, "Traversing Between Modes in Function Space for Fast Ensembling," ICML, 2023
H. Kim, H. Lee, H. Yang, and J. Lee, "Regularizing Towards Soft Equivariance Under Mixed Symmetries," ICML, 2023
H. Lee, E. Yun, G. Nam, E. Fong, and J. Lee, "Martingale Posterior Neural Processes," ICLR (Spotlight), 2023
G. Nam, H. Lee, B. Heo, and J. Lee, "Improving ensemble distillation with weight averaging and diversifying perturbation," ICML, 2022
H. Lee, E. Yun, H. Yang, and J. Lee, "Scale Mixture of Neural Network Gaussian Processes," ICLR, 2022