| 2025 | ICLR | Parameter Expanded Stochastic Gradient Markov Chain Monte Carlo. | Hyunsu Kim, Giung Nam, Chulhee Yun, Hongseok Yang, Juho Lee |
| 2025 | ICML | Ensemble Distribution Distillation via Flow Matching. | Jonggeon Park, Giung Nam, Hyunsu Kim, Jongmin Yoon, Juho Lee |
| 2024 | ICLR | Sparse Weight Averaging with Multiple Particles for Iterative Magnitude Pruning. | Moonseok Choi, Hyungi Lee, Giung Nam, Juho Lee |
| 2024 | ICLR | Enhancing Transfer Learning with Flexible Nonparametric Posterior Sampling. | Hyungi Lee, Giung Nam, Edwin Fong, Juho Lee |
| 2024 | ICLR | Lipsum-FT: Robust Fine-Tuning of Zero-Shot Models Using Random Text Guidance. | Giung Nam, Byeongho Heo, Juho Lee |
| 2023 | ICLR | Martingale Posterior Neural Processes. | Hyungi Lee, Eunggu Yun, Giung Nam, Edwin Fong, Juho Lee |
| 2023 | ICLR | Decoupled Training for Long-Tailed Classification With Stochastic Representations. | Giung Nam, Sunguk Jang, Juho Lee |
| 2023 | ICML | Traversing Between Modes in Function Space for Fast Ensembling. | Eunggu Yun, Hyungi Lee, Giung Nam, Juho Lee |
| 2022 | ICML | Improving Ensemble Distillation With Weight Averaging and Diversifying Perturbation. | Giung Nam, Hyungi Lee, Byeongho Heo, Juho Lee |