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A paper authored by our lab members is accepted at CVPR-21. – Ali Tousi, Haedong Jeong, Jiyeon Han, Hwanil Choi and Jaesik Choi, Automatic Correction of Internal Units in Generative Neural Networks, IEEE/CVF Conference on Computer Vision and Pattern Recognition… Continue Reading →
A paper, Prof. Jaesik Choi worked as a co-corresponding author, is accepted at ACS Analytical Chemistry [IF 6.785] Hyunbin Kim, Hae Nim Lee, Jaesik Choi*, Jihye Seong*, Spatiotemporal characterization of GPCR activity and function during endosomal trafficking pathway, ACS Analytical… Continue Reading →
Anh Tong successfully defended his PhD thesis, first in the lab! Congratulations Dr. Tong! With SAIL members, Anh has led to publish 5 papers in top AI conferences (ICML, IJCAI and AAAI)!
Our team won the AI competition (the 1st place in the general (non-commercial) track) hosted by the Korea East West Power.
SAIL members, Kyunghwan, Cheongwoong and Soonjae, won the second award at the 2020 ETRI Open API Use Case Contest Competition! Congratulations!! https://aiopen.etri.re.kr/intro_notice_view.php?wr_id=90
Three papers authored by our lab members are accepted at AAAI-21. – Anh Tong, Toan Tran, Hung Bui and Jaesik Choi, Learning Compositional Sparse Gaussian Processes with a Shrinkage Prior, AAAI Conference on Artificial Intelligence (AAAI), 2021. – Anh Tong… Continue Reading →
Prof. Choi’s online lecture will be broadcasted at 8pm (KST) in the following link, Youtube – https://www.youtube.com/watch?v=MMQjmeTmoxQ NAVER – https://tv.naver.com/kaos https://ikaos.org/kaos/apply/view.php?kc_idx=79 Intro Video: https://www.youtube.com/watch?v=7Czt2xTQNmY
A paper is accepted at ICAIF-2020. Youngjin Park, Deokjun Eom, and Jaesik Choi, Improved Predictive Deep Temporal Neural Networks with Trend Filtering, ICAIF-2020
KAIST AI대학원 확률형 인공지는 연구실에서 수행하는 연구(시계열 데이터 분석 및 설명가능 인공지능)에 관심있는 지원자는 이력서(CV)를 jaesik.choi@kaist.ac.kr로 지원 부탁드립니다. 관심있는 지원자를 위해서 다음과 같은 FAQ를 준비했습니다. https://docs.google.com/document/d/1Y7nZnkSMRI4uB9WJTTsmCyR-mVM3Z4plQ9_wJlYMadY/edit?usp=sharing If you are interested in research (time series analysis and explainable AI) at SAIL@KAIST,… Continue Reading →
A tutorial proposed to KDD 2020, Interpreting and Explaining Deep Neural Networks: A Perspective on Time Series Data, is accepted.
