Outlier detection

Robust learning for distributional shifts

Synthetic data generation & Data privacy

Deep generative models

M.Kang, S.Park, and D.Kim. (2026) "Memorize Early, Then Query: Inlier-Memorization-Guided Active Outlier Detection". The 40th AAAI Conference on Artificial Intelligence (AAAI 2026). 

D.Kim, F.J.Vanheusden, and A.Kim. (2025) "Forecasting cryptocurrency markets using recurrence and time-frequency analysis-based machine learning algorithms". Finance Research Letters. 

(Oral) S.Cho, J.Hwang, G.Bak, and D.Kim. (2025) "ALTBI: Constructing Improved Outlier Detection Models via Optimization of Inlier-Memorization Effect". The 39th AAAI Conference on Artificial Intelligence (AAAI 2025). 

D.Kim, J.Hwang, J.Lee, K.Kim, and Y.Kim. (2024) "ODIM: Outlier Detection via Likelihood of Under-Fitted Generative Models". The 41st International Conference on Machine Learning (ICML 2024).  

D.Kim, Y.Choi, K.Kim, and Y.Kim. (2024) "IOFM: Using the Interpolation Technique on Over-fitted Models to Identify Clean-annotated Samples". The 38th AAAI Conference on Artificial Intelligence (AAAI 2024).