Hankook Lee

C: Conference / W: Workshop / P: Preprint / *: equal contribution

[W] Fragment-based Multi-view Molecular Contrastive Learning

Seojin Kim*, Jaehyun Nam*, Junsu Kim, Hankook Lee, Sungsoo Ahn, Jinwoo Shin
ICLR Workshop on Machine Learning for Materials (ML4Materials), 2023

[C13] Enhancing Multiple Reliability Measures via Nuisance-extended Information Bottleneck

Jongheon Jeong, Sihyun Yu, Hankook Lee, Jinwoo Shin
Computer Vision and Pattern Recognition (CVPR), 2023
ECCV Workshop on Out-of-distribution Generalization in Computer Vision (ECCVW-OOD-CV), 2022

[C12] STUNT: Few-shot Tabular Learning with Self-generated Tasks from Unlabeled Tables

Jaehyun Nam, Jihoon Tack, Kyungmin Lee, Hankook Lee, Jinwoo Shin
International Conference on Learning Representations (ICLR), Spotlight presentation, 2023
Neural Information Processing Systems Workshop on Table Representation Learning (NeurIPSW-TRL), 2022
Samsung Humantech Paper Awards, Bronze Prize, 2023
[paper] [code]

[C11] Unsupervised Meta-learning via Few-shot Pseudo-supervised Contrastive Learning

Huiwon Jang*, Hankook Lee*, Jinwoo Shin
International Conference on Learning Representations (ICLR), Spotlight presentation, 2023
Neural Information Processing Systems Workshop on Meta-Learning (NeurIPSW-MetaLearn), 2022
[paper] [arxiv] [code]

[C10] Guiding Energy-based Models via Contrastive Latent Variables

Hankook Lee, Jongheon Jeong, Sejun Park, Jinwoo Shin
International Conference on Learning Representations (ICLR), Spotlight presentation, 2023
Neural Information Processing Systems Workshop on Self-Supervised Learning (NeurIPSW-SSL), Oral Presentation, 2022
[paper] [arxiv] [code]

[C9] Meta-Learning with Self-Improving Momentum Target

Jihoon Tack, Jongjin Park, Hankook Lee, Jaeho Lee, Jinwoo Shin
Neural Information Processing Systems (NeurIPS), 2022
[paper] [arxiv] [slide] [poster] [code]

[C8] Patch-level Representation Learning for Self-supervised Vision Transformers

Sukmin Yun, Hankook Lee, Jaehyung Kim, Jinwoo Shin
Computer Vision and Pattern Recognition (CVPR), Oral Presentation, 2022
[paper] [arxiv] [poster] [code]

[C7] Improving Transferability of Representations via Augmentation-Aware Self-Supervision

Hankook Lee, Kibok Lee, Kimin Lee, Honglak Lee, Jinwoo Shin
Neural Information Processing Systems (NeurIPS), 2021
ICML 2021 Workshop: Self-Supervised Learning for Reasoning and Perception
[paper] [arxiv] [slide] [poster] [code]

[C6] Self-Improved Retrosynthetic Planning

Junsu Kim, Sungsoo Ahn, Hankook Lee, Jinwoo Shin
International Conference on Machine Learning (ICML), 2021
[paper] [arxiv] [slide] [poster] [code]

[C5] RetCL: A Selection-based Approach for Retrosynthesis via Contrastive Learning

Hankook Lee, Sungsoo Ahn, Seung-Woo Seo, You Young Song, Eunho Yang, Sung Ju Hwang, Jinwoo Shin
International Joint Conference on Artificial Intelligence (IJCAI), 2021
NeurIPS Workshop for Machine Learning for Molecules, 2020
[paper] [arxiv (long version)] [slide] [poster] [code]

[C4] GTA: Graph Truncated Attention for Retrosynthesis

Seung-Woo Seo*, You Young Song*, June Yong Yang, Seohui Bae, Hankook Lee, Jinwoo Shin, Sung Ju Hwang, Eunho Yang
AAAI Conference on Artificial Intelligence (AAAI), 2021
[paper]

[C3] Guiding Deep Molecular Optimization with Genetic Exploration

Sungsoo Ahn, Junsu Kim, Hankook Lee, Jinwoo Shin
Neural Information Processing Systems (NeurIPS), 2020
[paper] [arxiv] [code]

[C2] Self-supervised Label Augmentation via Input Transformations

Hankook Lee, Sung Ju Hwang, Jinwoo Shin
International Conference on Machine Learning (ICML), 2020
Qualcomm-KAIST Innovation Awards, 2019
[paper] [arxiv] [code] [talk]

[C1] Learning What and Where to Transfer

Yunhun Jang*, Hankook Lee*, Sung Ju Hwang, Jinwoo Shin
International Conference on Machine Learning (ICML), 2019
[paper] [arxiv] [code] [slide] [talk 55:14~59:09]

[P1] Anytime Neural Prediction via Slicing Networks Vertically

Hankook Lee, Jinwoo Shin
arXiv, 2018
[arxiv] [code]