Title Author Date Journal Publication
Distilled Gradient Aggregation: Purify Features for Input Attribution in the Deep Neural Network Giyoung Jeon, Haedong Jeong and Jaesik Choi 2022-11-28 NeurIPS 2022 UNIST, KAIST, INEEJI
Learning Fractional White Noises in Neural Stochastic Differential Equations Anh Tong, Thanh Nguyen-Tang, Toan Tran and Jaesik Choi 2022-11-28 NeurIPS 2022 KAIST, VinAI Research, INEEJI, Johns Hopkins University
Can We Find Neurons that Cause Unrealistic Images in Deep Generative Networks? Hwanil Choi, Wonjoon Chang and Jaesik Choi 2022-01-17 IJCAI 2022 KAIST, INEEJI
Cooperative Multi-Robot Task Allocation with Reinforcement Learning Bumjin Park, Cheongwoong Kang, Jaesik Choi 2021-12-28 Sensors 2022 KAIST
Scheduling PID Attitude and Position Control Frequencies for Time-Optimal Quadrotor Waypoint Track Cheongwoong Kang, Bumjin Park, Jaesik Choi 2021-12-27 Sensors 2022 KAIST
Efficient Contrastive Learning via Novel Data Augmentation andCurriculum Learning Seonghyeon Ye, Jiseon Kim, Alice Oh 2021-11-07 EMNLP 2021 KAIST
Knowledge-Enhanced Evidence Retrieval for Counterargument Generation Yohan Jo, Haneul Yoo, JinYeong Bak, Alice Oh, Chris Reed, Eduard Hovy 2021-11-07 EMNLP 2021 CMU, KAIST, SKKU, University of Dundee
Distilling Linguistic Context for Language Model Compression Geondo Park, Gyeongman Kim, Eunho Yang 2021-11-07 EMNLP 2021 KAIST, AITRICS
Cluster-Promoting Quantization with Bit-Drop for Minimizing Network Quantization Loss Jung Hyun Lee, Jihun Yun, Sung Ju Hwang, Eunho Yang 2021-10-12 ICCV 2021 KAIST, AITRICS
Uncertainty-Aware Human Mesh Recovery from Video by Learning Part-Based 3D Dynamics Gun-Hee Lee, Seong-Whan Lee 2021-10-11 ICCV 2021 Korea Univ.