Enhanced neural machine translation by learning from draft. - Aodong Li; Shiyue Zhang 001; Dong Wang 013; Thomas Fang Zheng (APSIPA, 2017)

Variational Beam Search for Online Learning with Distribution Shifts. - Aodong Li; Alex Boyd; Padhraic Smyth; Stephan Mandt (CoRR, 2020)

Detecting and Adapting to Irregular Distribution Shifts in Bayesian Online Learning. - Aodong Li; Alex Boyd; Padhraic Smyth; Stephan Mandt (NeurIPS, 2021)

Latent Outlier Exposure for Anomaly Detection with Contaminated Data. - Chen Qiu 001; Aodong Li; Marius Kloft; Maja Rudolph; Stephan Mandt (ICML, 2022)

Deep Anomaly Detection under Labeling Budget Constraints. - Aodong Li; Chen Qiu 001; Marius Kloft; Padhraic Smyth; Stephan Mandt; Maja Rudolph (ICML, 2023)

Zero-Shot Anomaly Detection via Batch Normalization. - Aodong Li; Chen Qiu 001; Marius Kloft; Padhraic Smyth; Maja Rudolph; Stephan Mandt (NeurIPS, 2023)

Zero-Shot Anomaly Detection without Foundation Models. - Aodong Li; Chen Qiu 001; Marius Kloft; Padhraic Smyth; Maja Rudolph; Stephan Mandt (CoRR, 2023)

Model Selection of Anomaly Detectors in the Absence of Labeled Validation Data. - Clement Fung; Chen Qiu 001; Aodong Li; Maja Rudolph (CoRR, 2023)

Anomaly Detection of Tabular Data Using LLMs. - Aodong Li; Yunhan Zhao; Chen Qiu 001; Marius Kloft; Padhraic Smyth; Maja Rudolph; Stephan Mandt (CoRR, 2024)

Deep Anomaly Detection and Distribution Shifts - Aodong Li (2024)