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2020 – today
- 2023
[j2]Jing Zhang, Jiaqiang Du, Shifeng Fang, Zhilu Sheng, Yangchengsi Zhang, Bingqing Sun, Jialin Mao, Lijuan Li
:
Dynamic Changes, Spatiotemporal Differences, and Ecological Effects of Impervious Surfaces in the Yellow River Basin, 1986-2020. Remote. Sens. 15(1): 268 (2023)- [j1]Bingqing Sun, Jiaqiang Du, Fangfang Chong, Lijuan Li, Xiaoqian Zhu, Guangqing Zhai, Zebang Song, Jialin Mao:
Spatio-Temporal Variation and Prediction of Carbon Storage in Terrestrial Ecosystems in the Yellow River Basin. Remote. Sens. 15(15): 3866 (2023) - [c9]Rahul Ramesh, Jialin Mao, Itay Griniasty, Rubing Yang, Han Kheng Teoh, Mark K. Transtrum, James P. Sethna, Pratik Chaudhari:
A Picture of the Space of Typical Learnable Tasks. ICML 2023: 28680-28700 - [i6]Jialin Mao, Itay Griniasty, Han Kheng Teoh, Rahul Ramesh, Rubing Yang, Mark K. Transtrum, James P. Sethna, Pratik Chaudhari:
The Training Process of Many Deep Networks Explores the Same Low-Dimensional Manifold. CoRR abs/2305.01604 (2023) - 2022
- [c8]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:
A Framework for Generating Synthetic Clinical Datasets with Learning Effects to Support Methods Development and Validation. AMIA 2022 - [c7]Jejo D. Koola, Jialin Mao, Sharon E. Davis, Henry Ssemaganda, Dax M. Westerman, Lucila Ohno-Machado, Frederic S. Resnic, Michael E. Matheny:
A Framework for Detecting Medical Device Safety Signals Confounded by Learning Effects Using Machine Learning. AMIA 2022 - [c6]Jialin Mao, Michael Matheny, Philip Goodney, Art Sedrakyan:
Using Linked Registry-Electronic Health Records to Examine Long-term Outcomes of Medical Devices. AMIA 2022 - [c5]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:
Disentangling and Characterizing Device Safety Signals and Learning Effects. AMIA 2022 - [c4]Rubing Yang, Jialin Mao, Pratik Chaudhari:
Does the Data Induce Capacity Control in Deep Learning? ICML 2022: 25166-25197 - [c3]Zhiqi Bu, Jialin Mao, Shiyun Xu:
Scalable and Efficient Training of Large Convolutional Neural Networks with Differential Privacy. NeurIPS 2022 - [i5]Zhiqi Bu, Jialin Mao, Shiyun Xu:
Scalable and Efficient Training of Large Convolutional Neural Networks with Differential Privacy. CoRR abs/2205.10683 (2022) - [i4]Rahul Ramesh, Jialin Mao, Itay Griniasty, Rubing Yang, Han Kheng Teoh, Mark K. Transtrum, James P. Sethna, Pratik Chaudhari:
A picture of the space of typical learnable tasks. CoRR abs/2210.17011 (2022) - 2021
- [i3]Rubing Yang, Jialin Mao, Pratik Chaudhari:
Does the Data Induce Capacity Control in Deep Learning? CoRR abs/2110.14163 (2021)
2010 – 2019
- 2018
- [c2]Sean Welleck, Zixin Yao, Yu Gai, Jialin Mao, Zheng Zhang, Kyunghyun Cho:
Loss Functions for Multiset Prediction. NeurIPS 2018: 5788-5797 - 2017
- [c1]Sean Welleck, Jialin Mao, Kyunghyun Cho, Zheng Zhang:
Saliency-based Sequential Image Attention with Multiset Prediction. NIPS 2017: 5173-5183 - [i2]Sean Welleck, Jialin Mao, Kyunghyun Cho, Zheng Zhang:
Saliency-based Sequential Image Attention with Multiset Prediction. CoRR abs/1711.05165 (2017) - [i1]Sean Welleck, Zixin Yao, Yu Gai, Jialin Mao, Zheng Zhang, Kyunghyun Cho:
Loss Functions for Multiset Prediction. CoRR abs/1711.05246 (2017)
Coauthor Index
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