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A collaborative work on explainable artificial intelligence received recognition by Samsung.
Haedong Jeong successfully defended his PhD thesis, Example-based Methods to Explain the Internal Generative Mechanism of Deep Generative Neural Networks. Congratulations Dr. Jeong!
Our paper, Can We Find Neurons that Cause Unrealistic Images in Deep Generative Networks?, written by Hwanil Choi, Wonjoon Chang, Jaesik Choi is accepted at IJCAI-2022.
The KAIST Explainable Artificial Intelligence Center is selected by the Ministry of Science and ICT to host a new XAI project (13 Billion KRW, 130억원/5년), Development of Plug and Play Explainable Artificial Intelligence Platform, for the next 57 months.
Our paper, An Unsupervised Way to Understand Artifact Generating Internal Units in Generative Neural Networks, written by Haedong Jeong, Jiyeon Han and Jaesik Choi is accepted at AAAI-2022.
Prof. Choi received a prestigious POSCO Open and Collaboration (O&C) Award at the 33rd POSCO Annual Technical Conference for his contribution of explainable AI research in the POSCO smart factory.
KAIST XAI center, led by Prof. Jaesik Choi, made an MOU with IBK Bank for the research and education of explainable AI.
A new book, An Introduction to Lifted Probabilistic Inference edited by Guy Van den Broeck, Kristian Kersting and Sriraam Natarajan, on probabilistic inference is available at MIT press. Prof. Jaesik Choi contributed to write two book chapters “6 Lifted Aggregation… Continue Reading →
Our joint work with Prof. Yuseong Jung’s lab at KAIST is accepted at Chemical Science [IF 9.825] Juhwan Kim, Geun Ho Gu, Juhwan Noh, Seongun Kim, Suji Gim, Jaesik Choi* and Yousung Jung*, Predicting Potentially Hazardous Chemical Reactions Using Explainable… Continue Reading →
Our paper “Explaining the Decisions of Deep Policy Networks for Robotic Manipulations” written by Seongun Kim and Jaesik Choi is accepted to be presented at 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)!
