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ORCIDBrandon Edwards
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2020 – today
- 2024
[j2]Sarthak Pati
, Sourav Kumar, Amokh Varma, Brandon Edwards, Charles Lu, Liangqiong Qu, Justin J. Wang, Anantharaman Lakshminarayanan, Shih-han Wang, Micah J. Sheller, Ken Chang, Praveer Singh, Daniel L. Rubin, Jayashree Kalpathy-Cramer, Spyridon Bakas:
Privacy preservation for federated learning in health care. Patterns 5(7): 100974 (2024)- [j1]Guang Yang, Brandon Edwards, Spyridon Bakas, Qi Dou, Daguang Xu, Xiaoxiao Li, Wanying Wang:
Federated learning as a catalyst for digital healthcare innovations. Patterns 5(7): 101026 (2024) - [c3]Hongyan Chang, Brandon Edwards, Anindya S. Paul, Reza Shokri:
Efficient Privacy Auditing in Federated Learning. USENIX Security Symposium 2024 - [i7]Panyi Dong, Zhiyu Quan, Brandon Edwards, Hans Shih-Han Wang, Runhuan Feng, Tianyang Wang, Patrick Foley, Prashant Shah:
Privacy-Enhancing Collaborative Information Sharing through Federated Learning - A Case of the Insurance Industry. CoRR abs/2402.14983 (2024) - 2023
- [c2]Ahmet Faruk Saz, Yashas Malur Saidutta, Faramarz Fekri, Mustafa Riza Akdeniz, Brandon Edwards, Nageen Himayat:
Attri-Fed: A GIB Framework for Attribute-Based Privacy and Communication-Efficient Federated Learning. SPAWC 2023: 366-370 - 2022
- [i6]Sarthak Pati, Ujjwal Baid, Brandon Edwards, Micah J. Sheller, Hans Shih-Han Wang, G. Anthony Reina, Patrick Foley, Alexey Gruzdev, Deepthi Karkada, Christos Davatzikos, Chiharu Sako, Satyam Ghodasara, Michel Bilello, Suyash Mohan, Philipp Vollmuth, Gianluca Brugnara, Chandrakanth J. Preetha, Felix Sahm, Klaus H. Maier-Hein, Maximilian Zenk, Martin Bendszus, Wolfgang Wick, Evan Calabrese, Jeffrey D. Rudie, Javier E. Villanueva-Meyer, Soonmee Cha, Madhura Ingalhalikar, Manali Jadhav, Umang Pandey, Jitender Saini, John Garrett, Matthew Larson, Robert Jeraj, Stuart Currie, Russell Frood, Kavi Fatania, Raymond Y. Huang, Ken Chang, Carmen Balaña Quintero, Jaume Capellades, Josep Puig, Johannes Trenkler, Josef Pichler, Georg Necker, Andreas Haunschmidt, Stephan Meckel, Gaurav Shukla, Spencer Liem, Gregory S. Alexander, et al.:
Federated Learning Enables Big Data for Rare Cancer Boundary Detection. CoRR abs/2204.10836 (2022) - 2021
- [i5]Sarthak Pati, Siddhesh P. Thakur, Megh Bhalerao, Ujjwal Baid, Caleb M. Grenko, Brandon Edwards, Micah J. Sheller, Jose Agraz, Bhakti Baheti, Vishnu Bashyam, Parth Sharma, Babak Haghighi, Aimilia Gastounioti, Mark Bergman, Bjoern H. Menze, Despina Kontos, Christos Davatzikos, Spyridon Bakas:
GaNDLF: A Generally Nuanced Deep Learning Framework for Scalable End-to-End Clinical Workflows in Medical Imaging. CoRR abs/2103.01006 (2021) - [i4]Sarthak Pati, Ujjwal Baid, Maximilian Zenk, Brandon Edwards, Micah J. Sheller, G. Anthony Reina, Patrick Foley, Alexey Gruzdev, Jason Martin, Shadi Albarqouni, Yong Chen, Russell Taki Shinohara, Annika Reinke, David Zimmerer, John B. Freymann, Justin S. Kirby, Christos Davatzikos, Rivka R. Colen, Aikaterini Kotrotsou, Daniel S. Marcus, Mikhail Milchenko, Arash Nazeri, Hassan M. Fathallah-Shaykh, Roland Wiest, András Jakab, Marc-André Weber, Abhishek Mahajan, Lena Maier-Hein, Jens Kleesiek, Bjoern H. Menze, Klaus H. Maier-Hein, Spyridon Bakas:
The Federated Tumor Segmentation (FeTS) Challenge. CoRR abs/2105.05874 (2021) - [i3]G. Anthony Reina, Alexey Gruzdev, Patrick Foley, Olga Perepelkina, Mansi Sharma, Igor Davidyuk, Ilya Trushkin, Maksim Radionov, Aleksandr Mokrov, Dmitry Agapov, Jason Martin, Brandon Edwards, Micah J. Sheller, Sarthak Pati, Prakash Narayana Moorthy, Hans Shih-Han Wang, Prashant Shah, Spyridon Bakas:
OpenFL: An open-source framework for Federated Learning. CoRR abs/2105.06413 (2021) - 2020
- [i2]Hans Shih-Han Wang, Cory Cornelius, Brandon Edwards, Jason Martin:
Toward Few-step Adversarial Training from a Frequency Perspective. CoRR abs/2010.06545 (2020)
2010 – 2019
- 2018
- [c1]Micah J. Sheller, G. Anthony Reina, Brandon Edwards, Jason Martin, Spyridon Bakas:
Multi-institutional Deep Learning Modeling Without Sharing Patient Data: A Feasibility Study on Brain Tumor Segmentation. BrainLes@MICCAI (1) 2018: 92-104 - [i1]Micah J. Sheller, G. Anthony Reina, Brandon Edwards, Jason Martin, Spyridon Bakas:
Multi-Institutional Deep Learning Modeling Without Sharing Patient Data: A Feasibility Study on Brain Tumor Segmentation. CoRR abs/1810.04304 (2018)
Coauthor Index
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last updated on 2024-08-23 18:36 CEST by the dblp team
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