Source localization for hazardous material release in an outdoor chemical plant via a combination of LSTM-RNN and CFD simulation. - Hyunseung Kim; Myeongnam Park; Chang Won Kim; Dongil Shin (Comput. Chem. Eng., 2019)

Generative chemical transformer: attention makes neural machine learn molecular geometric structures via text. - Hyunseung Kim; Jonggeol Na; Won Bo Lee (CoRR, 2021)

Generative Chemical Transformer: Neural Machine Learning of Molecular Geometric Structures from Chemical Language via Attention. - Hyunseung Kim; Jonggeol Na; Won Bo Lee (J. Chem. Inf. Model., 2021)

DraftRec: Personalized Draft Recommendation for Winning in Multi-Player Online Battle Arena Games. - Hojoon Lee; Dongyoon Hwang; Hyunseung Kim; Byungkun Lee; Jaegul Choo (WWW, 2022)

Learning to Discover Skills through Guidance. - Hyunseung Kim; Byungkun Lee; Hojoon Lee; Dongyoon Hwang; Sejik Park; Kyushik Min; Jaegul Choo (NeurIPS, 2023)

PLASTIC: Improving Input and Label Plasticity for Sample Efficient Reinforcement Learning. - Hojoon Lee; Hanseul Cho 002; Hyunseung Kim; Daehoon Gwak; Joonkee Kim; Jaegul Choo; Se-Young Yun; Chulhee Yun (NeurIPS, 2023)

Materials Discovery with Extreme Properties via AI-Driven Combinatorial Chemistry. - Hyunseung Kim; Haeyeon Choi; Dongju Kang; Won Bo Lee; Jonggeol Na (CoRR, 2023)

Enhancing Generalization and Plasticity for Sample Efficient Reinforcement Learning. - Hojoon Lee; Hanseul Cho 002; Hyunseung Kim; Daehoon Gwak; Joonkee Kim; Jaegul Choo; Se-Young Yun; Chulhee Yun (CoRR, 2023)

Adapting Pretrained ViTs with Convolution Injector for Visuo-Motor Control. - Dongyoon Hwang; Byungkun Lee; Hojoon Lee; Hyunseung Kim; Jaegul Choo (ICML, 2024)

Slow and Steady Wins the Race: Maintaining Plasticity with Hare and Tortoise Networks. - Hojoon Lee; Hyeonseo Cho; Hyunseung Kim; Donghu Kim; Dugki Min; Jaegul Choo; Clare Lyle (ICML, 2024)

13.8 A 1a-nm 1.05V 10.5Gb/s/pin 16Gb LPDDR5 Turbo DRAM with WCK Correction Strategy, a Voltage-Offset-Calibrated Receiver and Parasitic Capacitance Reduction. - Yangho Seo; Jihee Choi; Sunki Cho; Hyunwook Han; Wonjong Kim; Gyeongha Ryu; Jungil Ahn; Younga Cho; Sungphil Choi; Seohee Lee; Wooju Lee; Chaehyuk Lee; et al. (ISSCC, 2024)

Do's and Don'ts: Learning Desirable Skills with Instruction Videos. - Hyunseung Kim; Byungkun Lee; Hojoon Lee; Dongyoon Hwang; Donghu Kim; Jaegul Choo (NeurIPS, 2024)

Multitask Extension of Geometrically Aligned Transfer Encoder. - Sung Moon Ko; Sumin Lee; Dae-Woong Jeong; Hyunseung Kim; Chanhui Lee; Soorin Yim; Sehui Han (CoRR, 2024)

Task Addition in Multi-Task Learning by Geometrical Alignment. - Soorin Yim; Dae-Woong Jeong; Sung Moon Ko; Sumin Lee; Hyunseung Kim; Chanhui Lee; Sehui Han (CoRR, 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)

SimBa: Simplicity Bias for Scaling Up Parameters in Deep Reinforcement Learning. - Hojoon Lee; Dongyoon Hwang; Donghu Kim; Hyunseung Kim; Jun Jet Tai; Kaushik Subramanian; Peter R. Wurman; Jaegul Choo; Peter Stone 001; Takuma Seno (ICLR, 2025)