Yun, Taeyoung

12 publications

TMLR 2026 Offline Model-Based Optimization: Comprehensive Review Minsu Kim, Jiayao Gu, Ye Yuan, Taeyoung Yun, Zixuan Liu, Yoshua Bengio, Can Chen

ICLR 2025 Adaptive Teachers for Amortized Samplers Minsu Kim, Sanghyeok Choi, Taeyoung Yun, Emmanuel Bengio, Leo Feng, Jarrid Rector-Brooks, Sungsoo Ahn, Jinkyoo Park, Nikolay Malkin, Yoshua Bengio

ICML 2025 Improved Off-Policy Reinforcement Learning in Biological Sequence Design Hyeonah Kim, Minsu Kim, Taeyoung Yun, Sanghyeok Choi, Emmanuel Bengio, Alex Hernández-Garcı́a, Jinkyoo Park

CVPR 2025 Learning to Sample Effective and Diverse Prompts for Text-to-Image Generation Taeyoung Yun, Dinghuai Zhang, Jinkyoo Park, Ling Pan

ICML 2025 Posterior Inference with Diffusion Models for High-Dimensional Black-Box Optimization Taeyoung Yun, Kiyoung Om, Jaewoo Lee, Sujin Yun, Jinkyoo Park

ICLRW 2025 Posterior Inference with Diffusion Models for High-Dimensional Black-Box Optimization Taeyoung Yun, Kiyoung Om, Jaewoo Lee, Sujin Yun, Jinkyoo Park

NeurIPS 2024 GTA: Generative Trajectory Augmentation with Guidance for Offline Reinforcement Learning Jaewoo Lee, Sujin Yun, Taeyoung Yun, Jinkyoo Park

NeurIPS 2024 Guided Trajectory Generation with Diffusion Models for Offline Model-Based Optimization Taeyoung Yun, Sujin Yun, Jaewoo Lee, Jinkyoo Park

NeurIPSW 2024 Improved Off-Policy Reinforcement Learning in Biological Sequence Design Hyeonah Kim, Minsu Kim, Taeyoung Yun, Sanghyeok Choi, Emmanuel Bengio, Alex Hernández-García, Jinkyoo Park

ICML 2024 Learning to Scale Logits for Temperature-Conditional GFlowNets Minsu Kim, Joohwan Ko, Taeyoung Yun, Dinghuai Zhang, Ling Pan, Woo Chang Kim, Jinkyoo Park, Emmanuel Bengio, Yoshua Bengio

ICLR 2024 Local Search GFlowNets Minsu Kim, Taeyoung Yun, Emmanuel Bengio, Dinghuai Zhang, Yoshua Bengio, Sungsoo Ahn, Jinkyoo Park

NeurIPSW 2023 Learning to Scale Logits for Temperature-Conditional GFlowNets Minsu Kim, Joohwan Ko, Dinghuai Zhang, Ling Pan, Taeyoung Yun, Woo Chang Kim, Jinkyoo Park, Yoshua Bengio