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Two papers are accepted at NeurIPS-2022. Anh Tong, Thanh Nguyen-Tang, Toan Tran and Jaesik Choi, Learning White Noises in Neural Stochastic Differential Equations Giyoung Jeon, Haedong Jeong and Jaesik Choi, Distilled Gradient Aggregation: Purify Features for Input Attribution in the… Continue Reading →
We have open positions for shot/long-terms AI researchers/SW Engineers. If you are interested in, please send your CV to jaesik.choi@kaist.ac.kr.
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 →
