Saliency-based Sequential Image Attention with Multiset Prediction. - Sean Welleck; Jialin Mao; Kyunghyun Cho; Zheng Zhang 001 (NIPS, 2017)

Loss Functions for Multiset Prediction. - Sean Welleck; Zixin Yao; Yu Gai; Jialin Mao; Zheng Zhang 001; Kyunghyun Cho (NeurIPS, 2018)

A Framework for Generating Synthetic Clinical Datasets with Learning Effects to Support Methods Development and Validation. - Sharon E. Davis; Henry Ssemaganda; Jejo Koola; Jialin Mao; Dax M. Westerman; Theodore Speroff; Usha Govindarajulu; Craig Ramsay; Lucila Ohno-Machado; Frederic S. Resnic; Michael E. Matheny (AMIA, 2022)

A Framework for Detecting Medical Device Safety Signals Confounded by Learning Effects Using Machine Learning. - Jejo D. Koola; Jialin Mao; Sharon E. Davis; Henry Ssemaganda; Dax M. Westerman; Lucila Ohno-Machado; Frederic S. Resnic; Michael E. Matheny (AMIA, 2022)

Using Linked Registry-Electronic Health Records to Examine Long-term Outcomes of Medical Devices. - Jialin Mao; Michael Matheny; Philip Goodney; Art Sedrakyan (AMIA, 2022)

Disentangling and Characterizing Device Safety Signals and Learning Effects. - Henry Ssemaganda; Frederic S. Resnic; Sharon E. Davis; Usha Govindarajulu; Jejo Koola; Jialin Mao; Dax M. Westerman; Theodore Speroff; Craig Ramsay; Art Sedrakyan; Lucila Ohno-Machado; Michael E. Matheny (AMIA, 2022)

Does the Data Induce Capacity Control in Deep Learning? - Rubing Yang; Jialin Mao; Pratik Chaudhari (ICML, 2022)

Scalable and Efficient Training of Large Convolutional Neural Networks with Differential Privacy. - Zhiqi Bu; Jialin Mao; Shiyun Xu (NeurIPS, 2022)

A Picture of the Space of Typical Learnable Tasks. - Rahul Ramesh; Jialin Mao; Itay Griniasty; Rubing Yang; Han Kheng Teoh; Mark K. Transtrum; James P. Sethna; Pratik Chaudhari (ICML, 2023)

The Training Process of Many Deep Networks Explores the Same Low-Dimensional Manifold. - Jialin Mao; Itay Griniasty; Han Kheng Teoh; Rahul Ramesh; Rubing Yang; Mark K. Transtrum; James P. Sethna; Pratik Chaudhari (CoRR, 2023)

Dynamic Changes, Spatiotemporal Differences, and Ecological Effects of Impervious Surfaces in the Yellow River Basin, 1986-2020. - Jing Zhang; Jiaqiang Du; Shifeng Fang; Zhilu Sheng; Yangchengsi Zhang; Bingqing Sun; Jialin Mao; Lijuan Li 003 (Remote. Sens., 2023)

Spatio-Temporal Variation and Prediction of Carbon Storage in Terrestrial Ecosystems in the Yellow River Basin. - Bingqing Sun; Jiaqiang Du; Fangfang Chong; Lijuan Li 003; Xiaoqian Zhu; Guangqing Zhai; Zebang Song; Jialin Mao (Remote. Sens., 2023)

A machine learning framework to adjust for learning effects in medical device safety evaluation. - Jejo D. Koola; Karthik Ramesh; Jialin Mao; Minyoung Ahn; Sharon E. Davis; Usha Govindarajulu; Amy Perkins; Dax M. Westerman; Henry Ssemaganda; Theodore Speroff; Lucila Ohno-Machado; Craig Ramsay; et al. (J. Am. Medical Informatics Assoc., 2025)

An Analytical Characterization of Sloppiness in Neural Networks: Insights from Linear Models. - Jialin Mao; Itay Griniasty; Yan Sun; Mark K. Transtrum; James P. Sethna; Pratik Chaudhari (CoRR, 2025)