Jialin Mao

According to our database, Jialin Mao authored at least 13 papers between 2017 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2025

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, Art Sedrakyan, Frederic S. Resnic, Michael E. Matheny

J. Am. Medical Informatics Assoc., 2025

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, Xiaoqian Zhu, Guangqing Zhai, Zebang Song, Jialin Mao

Remote. Sens., August, 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

Remote. Sens., January, 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

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

Proceedings of the International Conference on Machine Learning, 2023

2022

Scalable and Efficient Training of Large Convolutional Neural Networks with Differential Privacy.

Zhiqi Bu, Jialin Mao, Shiyun Xu

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Does the Data Induce Capacity Control in Deep Learning?

Rubing Yang, Jialin Mao, Pratik Chaudhari

Proceedings of the International Conference on Machine Learning, 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

Proceedings of the AMIA 2022, 2022

Using Linked Registry-Electronic Health Records to Examine Long-term Outcomes of Medical Devices.

Jialin Mao, Michael Matheny, Philip Goodney, Art Sedrakyan

Proceedings of the AMIA 2022, 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

Proceedings of the AMIA 2022, 2022

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

Proceedings of the AMIA 2022, 2022

2018

Loss Functions for Multiset Prediction.

Sean Welleck, Zixin Yao, Yu Gai, Jialin Mao, Zheng Zhang, Kyunghyun Cho

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2017

Saliency-based Sequential Image Attention with Multiset Prediction.

Sean Welleck, Jialin Mao, Kyunghyun Cho, Zheng Zhang

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017