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A paper, Beyond Single Path Integrated Gradients for Reliable Input Attribution via Randomized Path Sampling, written by Giyoung Jeon, Haedong Jeong and Jaesik Choi is accepted at ICCV-2023.
Seongun Kim, a PhD student of our lab, presented at Explainable Robotics Workshop at ICRA 2023 as an invited speaker.
Our paper, Variational Curriculum Reinforcement Learning for Unsupervised Discovery of Skills, written by Seongun Kim, Kyowoon Lee and Jaesik Choi is accepted at ICML-23.
Our paper, Rarity Score: A New Metric to Evaluate the Uncommonness of Synthesized Images, written by Jiyeon Han, Hwanil Choi, Yunjey Choi, Junho Kim, Jung-Woo Ha and Jaesik Choi is accepted at ICLR-23.
A paper, Adaptive and Explainable Deployment of Navigation Skills via Hierarchical Deep Reinforcement Learning, written by Kyowoon Lee, Seongun Kim and Jaesik Choi, is accepted at ICRA-23.
Prof. Choi presented the work at IPAM XAI Workshop held in UCLA. Explainable AI for the Sciences: Towards Novel Insights
Prof. Choi’s article, South Korea’s Response to Surging AI Use in the US and China, is published in Global Asia, a international relational magazine published by the East Asia Foundation.
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.
