Statistical Artificial Intelligence Lab@KAIST

Artificial Intelligence and Machine Learning Research



[News] The 1st Technical Briefing Session of the Seongnam Research Center of KAIST Graduate School of AI

KAIST AI대학원 성남연구센터 제1회 기술설명회가 2020년 10월 16일 금요일 13:00~18:00에 개최됩니다. 본 설명회는 Zoom을 이용해 온라인으로 개최됩니다. 사전신청을 통해 참가신청을 받고 있으며, 신청자에 한하여 개별상담도 진행됩니다. 포스터의 QR코드 또는 아래의 링크를 통해 사전신청이 가능합니다. – 사전 신청 링크:

[Paper] A paper is accepted ICAIF-2020

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

FAQ about Graduate Admission at KAIST (SAIL@KAIST 지원 정보)

KAIST AI대학원 확률형 인공지는 연구실에서 수행하는 연구(시계열 데이터 분석 및 설명가능 인공지능)에 관심있는 지원자는 이력서(CV)를로 지원 부탁드립니다. 관심있는 지원자를 위해서 다음과 같은 FAQ를 준비했습니다. If you are interested in research (time series analysis and explainable AI) at SAIL@KAIST,… Continue Reading →

[News] Our XAI tutorial proposal is accepted at KDD 2020!

A tutorial proposed to KDD 2020, Interpreting and Explaining Deep Neural Networks: A Perspective on Time Series Data, is accepted.

[Paper] A paper is accepted USENIX ACT 2020

A paper written by Nguyen T. Nguyen and Prof. Jaesik Choi in collaboration with Prof. Yong-ri Choi’s group and Prof. Sam H. Noh’s one is accepted at USENIX ATC 20. Jay H. Park, Gyeongchan Yun, Chang M. Yi, Nguyen T…. Continue Reading →

[Paper] A paper is accepted at ICRA 2020

A papers is accepted at ICRA-2020. YongHyeok Seo, Dongju Shin, Jaesik Choi, and Se Young Chun, A Single Multi-Task Deep Neural Network with Post-Processing for Object Detection with Reasoning and Robotic Grasp Detection, ICRA-2020 (pdf, video).

[Paper] XAI – Explainable artificial intelligence at Science Robotics

A perspective, review article, XAI – Explainable artificial intelligence, co-authored by Prof. Jaesik Choi with David Gunning (DARPA, currently at Facebook) and other researchers is published at Science Robotics.

[Award] NAVER PhD Fellowship

Anh Tong, a PhD student of UNIST, received NAVER PhD Fellowship award.

[Papers] Two papers are accepted at AAAI-2020

Two papers are accepted at AAAI-2020. Giyoung Jeon*, Haedong Jeong* and Jaesik Choi, An Efficient Explorative Sampling Considering the Generative Boundaries of Deep Generative Neural Networks, AAAI-2020 (Accepted, Oral, * contributed equally). Woojeong Nam, Shir Gur, Jaesik Choi, Lior Wolf… Continue Reading →

[Project] New Time Series Deep Learning Models to Diagnose Coal Powered Power Plants

Our research team ( successfully has finished a research project with Korea East-West Power Company to build time series deep learning models which diagnose tubes in Power Plant Boilers of the Dangjin power station. Our AI module and software are… Continue Reading →

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