Welcome to i-Stat Laboratory!
We are conducting research on deep learning from a statistical perspective. Currently, we focus on developing methods for semi-supervised learning on tabular datasets and are also interested in synthetic data generation and differential privacy. We are seeking undergraduate and graduate students who have a keen interest in deep learning. If you are confident in your skills in Python, statistics, and data science, we welcome your application.
News
(24/06/01) Minseo Kang is a new member of our lab. Welcome! 😊
(24/05/02) The paper titled "ODIM: Outlier Detection via Likelihood of Under-Fitted Generative Models" has been accepted at ICML 2024.
(24/03/18) Seven students joined our lab as undergraduate interns. Welcome! 😊
(24/03/13) We completed the winter seminar, where we reviewed recent papers on differential privacy, specifically DP-SGD.
(24/02/23) Dongha Kim presented his paper titled "IOFM: Using the Interpolation Technique on the Over-Fitted Models to Identify Clean-Annotated Samples" at AAAI 2024, held in Vancouver, Canada.