HeeSun Bae

According to our database, HeeSun Bae authored at least 8 papers between 2022 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2025

Preference Optimization by Estimating the Ratio of the Data Distribution.

Yeongmin Kim, HeeSun Bae, Byeonghu Na, Il-Chul Moon

CoRR, May, 2025

Distilling Dataset into Neural Field.

Donghyeok Shin, HeeSun Bae, Gyuwon Sim, Wanmo Kang, Il-Chul Moon

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

Unknown Domain Inconsistency Minimization for Domain Generalization.

Seungjae Shin, HeeSun Bae, Byeonghu Na, Yoon-Yeong Kim, Il-Chul Moon

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Label-Noise Robust Diffusion Models.

Byeonghu Na, Yeongmin Kim, HeeSun Bae, Jung Hyun Lee, Se Jung Kwon, Wanmo Kang, Il-Chul Moon

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Dirichlet-based Per-Sample Weighting by Transition Matrix for Noisy Label Learning.

HeeSun Bae, Seungjae Shin, Byeonghu Na, Il-Chul Moon

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Make Prompts Adaptable: Bayesian Modeling for Vision-Language Prompt Learning with Data-Dependent Prior.

Youngjae Cho, HeeSun Bae, Seungjae Shin, Yeo Dong Youn, Weonyoung Joo, Il-Chul Moon

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Loss-Curvature Matching for Dataset Selection and Condensation.

Seungjae Shin, HeeSun Bae, DongHyeok Shin, Weonyoung Joo, Il-Chul Moon

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

From Noisy Prediction to True Label: Noisy Prediction Calibration via Generative Model.

HeeSun Bae, Seungjae Shin, Byeonghu Na, JoonHo Jang, Kyungwoo Song, Il-Chul Moon

Proceedings of the International Conference on Machine Learning, 2022