Pulakesh Upadhyaya

According to our database, Pulakesh Upadhyaya authored at least 13 papers between 2017 and 2024.

Collaborative distances:

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

2024

Deep Representation Learning-Based Dynamic Trajectory Phenotyping for Acute Respiratory Failure in Medical Intensive Care Units.

Alan Wu, Tilendra Choudhary, Pulakesh Upadhyaya, Ayman Ali, Philip Yang, Rishikesan Kamaleswaran

CoRR, 2024

2023

ClotCatcher: a novel natural language model to accurately adjudicate venous thromboembolism from radiology reports.

Jeffrey Wang, Joao Souza de Vale, Saransh Gupta, Pulakesh Upadhyaya, Felipe A. Lisboa, Seth A. Schobel, Eric A. Elster, Christopher J. Dente, Timothy G. Buchman, Rishikesan Kamaleswaran

BMC Medical Informatics Decis. Mak., December, 2023

Emulate randomized clinical trials using heterogeneous treatment effect estimation for personalized treatments: Methodology review and benchmark.

Yaobin Ling, Pulakesh Upadhyaya, Luyao Chen, Xiaoqian Jiang, Yejin Kim

J. Biomed. Informatics, January, 2023

Inferring Personalized Treatment Effect of Antihypertensives on Alzheimer's Disease Using Deep Learning.

Pulakesh Upadhyaya, Yaobin Ling, Luyao Chen, Yejin Kim, Xiaoqian Jiang

Proceedings of the 11th IEEE International Conference on Healthcare Informatics, 2023

2021

Scalable Causal Structure Learning: New Opportunities in Biomedicine.

Pulakesh Upadhyaya, Kai Zhang, Can Li, Xiaoqian Jiang, Yejin Kim

CoRR, 2021

Heterogeneous Treatment Effect Estimation using machine learning for Healthcare application: tutorial and benchmark.

Yaobin Ling, Pulakesh Upadhyaya, Luyao Chen, Xiaoqian Jiang, Yejin Kim

CoRR, 2021

2020

Improve Robustness of Deep Neural Networks by Coding.

Kunping Huang, Netanel Raviv, Siddharth Jain, Pulakesh Upadhyaya, Jehoshua Bruck, Paul H. Siegel, Anxiao Andrew Jiang

Proceedings of the Information Theory and Applications Workshop, 2020

CodNN - Robust Neural Networks From Coded Classification.

Netanel Raviv, Siddharth Jain, Pulakesh Upadhyaya, Jehoshua Bruck, Anxiao Andrew Jiang

Proceedings of the IEEE International Symposium on Information Theory, 2020

2019

Machine Learning for Error Correction with Natural Redundancy.

Pulakesh Upadhyaya, Anxiao Jiang

CoRR, 2019

Representation-Oblivious Error Correction by Natural Redundancy.

Pulakesh Upadhyaya, Anxiao Andrew Jiang

Proceedings of the 2019 IEEE International Conference on Communications, 2019

2017

Correcting errors by natural redundancy.

Anxiao Jiang, Pulakesh Upadhyaya, Erich F. Haratsch, Jehoshua Bruck

Proceedings of the 2017 Information Theory and Applications Workshop, 2017

On LDPC decoding with natural redundancy.

Pulakesh Upadhyaya, Anxiao Andrew Jiang

Proceedings of the 55th Annual Allerton Conference on Communication, 2017

Stopping set elimination for LDPC codes.

Anxiao Andrew Jiang, Pulakesh Upadhyaya, Ying Wang, Krishna R. Narayanan, Hongchao Zhou, Jin Sima, Jehoshua Bruck

Proceedings of the 55th Annual Allerton Conference on Communication, 2017