Neural Stain-Style Transfer Learning using GAN for Histopathological Images. - Hyungjoo Cho; Sungbin Lim; Gunho Choi; Hyunseok Min (CoRR, 2017)

Uncertainty-Aware Learning from Demonstration Using Mixture Density Networks with Sampling-Free Variance Modeling. - Sungjoon Choi; Kyungjae Lee 001; Sungbin Lim; Songhwai Oh (ICRA, 2018)

ChoiceNet: Robust Learning by Revealing Output Correlations. - Sungjoon Choi; Sanghoon Hong; Sungbin Lim (CoRR, 2018)

Scalable Neural Architecture Search for 3D Medical Image Segmentation. - Sungwoong Kim; Ildoo Kim; Sungbin Lim; Woonhyuk Baek; Chiheon Kim; Hyungjoo Cho; Boogeon Yoon; Taesup Kim (MICCAI (3), 2019)

Fast AutoAugment. - Sungbin Lim; Ildoo Kim; Taesup Kim; Chiheon Kim; Sungwoong Kim (NeurIPS, 2019)

Tsallis Reinforcement Learning: A Unified Framework for Maximum Entropy Reinforcement Learning. - Kyungjae Lee 001; Sungyub Kim; Sungbin Lim; Sungjoon Choi; Songhwai Oh (CoRR, 2019)

Monte Carlo Tree Search in Continuous Spaces Using Voronoi Optimistic Optimization with Regret Bounds. - Beomjoon Kim; Kyungjae Lee 001; Sungbin Lim; Leslie Pack Kaelbling; Tomás Lozano-Pérez (AAAI, 2020)

Task Agnostic Robust Learning on Corrupt Outputs by Correlation-Guided Mixture Density Networks. - Sungjoon Choi; Sanghoon Hong; Kyungjae Lee 001; Sungbin Lim (CVPR, 2020)

Optimal Algorithms for Stochastic Multi-Armed Bandits with Heavy Tailed Rewards. - Kyungjae Lee 001; Hongjun Yang; Sungbin Lim; Songhwai Oh (NeurIPS, 2020)

Generalized Tsallis Entropy Reinforcement Learning and Its Application to Soft Mobile Robots. - Kyungjae Lee 001; Sungyub Kim; Sungbin Lim; Sungjoon Choi; Mineui Hong; Jae In Kim; Yong-Lae Park; Songhwai Oh (Robotics: Science and Systems, 2020)

torchgpipe: On-the-fly Pipeline Parallelism for Training Giant Models. - Chiheon Kim; Heungsub Lee; Myungryong Jeong; Woonhyuk Baek; Boogeon Yoon; Ildoo Kim; Sungbin Lim; Sungwoong Kim (CoRR, 2020)

AutoCLINT: The Winning Method in AutoCV Challenge 2019. - Woonhyuk Baek; Ildoo Kim; Sungwoong Kim; Sungbin Lim (CoRR, 2020)

Neural Bootstrapper. - Minsuk Shin; Hyungjoo Cho; Sungbin Lim (CoRR, 2020)

Evaluation of conditional treatment effects of adjuvant treatments on patients with synovial sarcoma using Bayesian subgroup analysis. - Sung Wook Seo; Jisoo Kim; Jihye Son; Sungbin Lim (BMC Medical Informatics Decis. Mak., 2020)

Neural Bootstrapper. - Minsuk Shin; Hyungjoo Cho; Hyun-seok Min; Sungbin Lim (NeurIPS, 2021)

A Deep Reinforcement Learning Approach for Solving the Traveling Salesman Problem with Drone. - Aigerim Bogyrbayeva; Taehyun Yoon; Hanbum Ko; Sungbin Lim; Hyokun Yun; Changhyun Kwon 001 (CoRR, 2021)

Bag of Tricks for In-Distribution Calibration of Pretrained Transformers. - Jaeyoung Kim; Dongbin Na; Sungchul Choi; Sungbin Lim (EACL (Findings), 2023)

Score-based Generative Modeling through Stochastic Evolution Equations in Hilbert Spaces. - Sungbin Lim; Eun-Bi Yoon; Taehyun Byun; Taewon Kang; Seungwoo Kim; Kyungjae Lee 001; Sungjoon Choi (NeurIPS, 2023)

Score-based Generative Models with Lévy Processes. - Eun-Bi Yoon; Keehun Park; Sungwoong Kim; Sungbin Lim (NeurIPS, 2023)

Threshold-aware Learning to Generate Feasible Solutions for Mixed Integer Programs. - Taehyun Yoon; Jinwon Choi; Hyokun Yun; Sungbin Lim (CoRR, 2023)

Can We Utilize Pre-trained Language Models within Causal Discovery Algorithms? - Chanhui Lee; Juhyeon Kim; Yongjun Jeong; Juhyun Lyu; Junghee Kim; Sangmin Lee; Sangjun Han; Hyeokjun Choe; Soyeon Park; Woohyung Lim; Sungbin Lim; Sanghack Lee (CoRR, 2023)

Stochastic Optimal Control for Diffusion Bridges in Function Spaces. - Byoungwoo Park; Jungwon Choi; Sungbin Lim; Juho Lee 001 (NeurIPS, 2024)

Slice and Conquer: A Planar-to-3D Framework for Efficient Interactive Segmentation of Volumetric Images. - Wonwoo Cho; Dongmin Choi; Hyesu Lim; Jinho Choi 005; Saemee Choi; Hyunseok Min; Sungbin Lim; Jaegul Choo (WACV, 2024)

Differentiation of glioblastoma from solitary brain metastasis using deep ensembles: Empirical estimation of uncertainty for clinical reliability. - Yae Won Park; Sujeong Eom; Seungwoo Kim; Sungbin Lim; Ji Eun Park; Ho Sung Kim; Seng Chan You; Sungsoo Ahn; Seung-Koo Lee (Comput. Methods Programs Biomed., 2024)

Scalable Multi-Task Transfer Learning for Molecular Property Prediction. - Chanhui Lee; Dae-Woong Jeong; Sung Moon Ko; Sumin Lee; Hyunseung Kim; Soorin Yim; Sehui Han; Sungwoong Kim; Sungbin Lim (CoRR, 2024)

Minimax Optimal Bandits for Heavy Tail Rewards. - Kyungjae Lee 001; Sungbin Lim (IEEE Trans. Neural Networks Learn. Syst., 2024)

Hierarchical Decomposition Framework for Steiner Tree Packing Problem. - Hanbum Ko; Minu Kim; Han-Seul Jeong; Sunghoon Hong; Deunsol Yoon; Youngjoon Park; Woohyung Lim; Honglak Lee; Moontae Lee; Kanghoon Lee; Sungbin Lim; Sungryull Sohn (ICORES, 2025)

Mol-LLM: Generalist Molecular LLM with Improved Graph Utilization. - Chanhui Lee; Yuheon Song; Yongjun Jeong; Hanbum Ko; Rodrigo Hormazabal; Sehui Han; Kyunghoon Bae; Sungbin Lim; Sungwoong Kim (CoRR, 2025)

CAST: Cross Attention based multimodal fusion of Structure and Text for materials property prediction. - Jaewan Lee; Changyoung Park; Hongjun Yang; Sungbin Lim; Sehui Han (CoRR, 2025)

Probability-Flow ODE in Infinite-Dimensional Function Spaces. - Kunwoo Na; Junghyun Lee; Se-Young Yun; Sungbin Lim (CoRR, 2025)

Score-informed Neural Operator for Enhancing Ordering-based Causal Discovery. - Jiyeon Kang; Songseong Kim; Chanhui Lee; Doyeong Hwang; Joanie Hayoun Chung; Yunkyung Ko; Sumin Lee; Sungwoong Kim; Sungbin Lim (CoRR, 2025)