Sharut Gupta

FL Games: A Federated Learning Framework for Distribution Shifts

Oct 31, 2022
Sharut Gupta, Kartik Ahuja, Mohammad Havaei, Niladri Chatterjee, Yoshua Bengio

Figure 2 for FL Games: A Federated Learning Framework for Distribution Shifts

Figure 3 for FL Games: A Federated Learning Framework for Distribution Shifts

* Accepted as ORAL at NeurIPS Workshop on Federated Learning: Recent Advances and New Challenges. arXiv admin note: text overlap with arXiv:2205.11101

Access Paper or Ask Questions

FL Games: A federated learning framework for distribution shifts

May 23, 2022
Sharut Gupta, Kartik Ahuja, Mohammad Havaei, Niladri Chatterjee, Yoshua Bengio

Access Paper or Ask Questions

Minimizing Client Drift in Federated Learning via Adaptive Bias Estimation

Apr 27, 2022
Farshid Varno, Marzie Saghayi, Laya Rafiee, Sharut Gupta, Stan Matwin, Mohammad Havaei

Figure 2 for Minimizing Client Drift in Federated Learning via Adaptive Bias Estimation

Figure 3 for Minimizing Client Drift in Federated Learning via Adaptive Bias Estimation

Figure 4 for Minimizing Client Drift in Federated Learning via Adaptive Bias Estimation

* AdaBest

Access Paper or Ask Questions

QU-BraTS: MICCAI BraTS 2020 Challenge on Quantifying Uncertainty in Brain Tumor Segmentation -- Analysis of Ranking Metrics and Benchmarking Results

Dec 19, 2021
Raghav Mehta, Angelos Filos, Ujjwal Baid, Chiharu Sako, Richard McKinley, Michael Rebsamen, Katrin Dätwyler, Raphael Meier, Piotr Radojewski, Gowtham Krishnan Murugesan, Sahil Nalawade, Chandan Ganesh, Ben Wagner, Fang F. Yu, Baowei Fei, Ananth J. Madhuranthakam, Joseph A. Maldjian, Laura Daza, Catalina Gómez, Pablo Arbeláez, Chengliang Dai, Shuo Wang, Hadrien Raynaud, Yuanhan Mo, Elsa Angelini, Yike Guo, Wenjia Bai, Subhashis Banerjee, Linmin Pei, Murat AK, Sarahi Rosas-González, Illyess Zemmoura, Clovis Tauber, Minh H. Vu, Tufve Nyholm, Tommy Löfstedt, Laura Mora Ballestar, Veronica Vilaplana, Hugh McHugh, Gonzalo Maso Talou, Alan Wang, Jay Patel, Ken Chang, Katharina Hoebel, Mishka Gidwani, Nishanth Arun, Sharut Gupta, Mehak Aggarwal, Praveer Singh, Elizabeth R. Gerstner, Jayashree Kalpathy-Cramer, Nicolas Boutry, Alexis Huard, Lasitha Vidyaratne, Md Monibor Rahman, Khan M. Iftekharuddin, Joseph Chazalon, Elodie Puybareau, Guillaume Tochon, Jun Ma, Mariano Cabezas, Xavier Llado, Arnau Oliver, Liliana Valencia, Sergi Valverde, Mehdi Amian, Mohammadreza Soltaninejad, Andriy Myronenko, Ali Hatamizadeh, Xue Feng, Quan Dou, Nicholas Tustison, Craig Meyer, Nisarg A. Shah, Sanjay Talbar, Marc-Andr Weber, Abhishek Mahajan, Andras Jakab, Roland Wiest, Hassan M. Fathallah-Shaykh, Arash Nazeri, Mikhail Milchenko, Daniel Marcus, Aikaterini Kotrotsou, Rivka Colen, John Freymann, Justin Kirby, Christos Davatzikos, Bjoern Menze, Spyridon Bakas, Yarin Gal, Tal Arbel

Figure 1 for QU-BraTS: MICCAI BraTS 2020 Challenge on Quantifying Uncertainty in Brain Tumor Segmentation -- Analysis of Ranking Metrics and Benchmarking Results

Figure 2 for QU-BraTS: MICCAI BraTS 2020 Challenge on Quantifying Uncertainty in Brain Tumor Segmentation -- Analysis of Ranking Metrics and Benchmarking Results

Figure 3 for QU-BraTS: MICCAI BraTS 2020 Challenge on Quantifying Uncertainty in Brain Tumor Segmentation -- Analysis of Ranking Metrics and Benchmarking Results

Figure 4 for QU-BraTS: MICCAI BraTS 2020 Challenge on Quantifying Uncertainty in Brain Tumor Segmentation -- Analysis of Ranking Metrics and Benchmarking Results

* Under submission at MELBA journal

Access Paper or Ask Questions

Addressing catastrophic forgetting for medical domain expansion

Mar 24, 2021
Sharut Gupta, Praveer Singh, Ken Chang, Liangqiong Qu, Mehak Aggarwal, Nishanth Arun, Ashwin Vaswani, Shruti Raghavan, Vibha Agarwal, Mishka Gidwani, Katharina Hoebel, Jay Patel, Charles Lu, Christopher P. Bridge, Daniel L. Rubin, Jayashree Kalpathy-Cramer

Figure 2 for Addressing catastrophic forgetting for medical domain expansion

Figure 3 for Addressing catastrophic forgetting for medical domain expansion

Figure 4 for Addressing catastrophic forgetting for medical domain expansion

* First three authors contributed equally

Access Paper or Ask Questions

The unreasonable effectiveness of Batch-Norm statistics in addressing catastrophic forgetting across medical institutions

Nov 16, 2020
Sharut Gupta, Praveer Singh, Ken Chang, Mehak Aggarwal, Nishanth Arun, Liangqiong Qu, Katharina Hoebel, Jay Patel, Mishka Gidwani, Ashwin Vaswani, Daniel L Rubin, Jayashree Kalpathy-Cramer

Figure 2 for The unreasonable effectiveness of Batch-Norm statistics in addressing catastrophic forgetting across medical institutions

Figure 3 for The unreasonable effectiveness of Batch-Norm statistics in addressing catastrophic forgetting across medical institutions

Figure 4 for The unreasonable effectiveness of Batch-Norm statistics in addressing catastrophic forgetting across medical institutions

* Accepted as oral presentation in Machine Learning for Health (ML4H) at NeurIPS 2020 - Extended Abstract ; 6 pages and 4 figures

Access Paper or Ask Questions

Towards Trainable Saliency Maps in Medical Imaging

Nov 15, 2020
Mehak Aggarwal, Nishanth Arun, Sharut Gupta, Ashwin Vaswani, Bryan Chen, Matthew Li, Ken Chang, Jay Patel, Katherine Hoebel, Mishka Gidwani, Jayashree Kalpathy-Cramer, Praveer Singh

Figure 2 for Towards Trainable Saliency Maps in Medical Imaging

Figure 3 for Towards Trainable Saliency Maps in Medical Imaging

Figure 4 for Towards Trainable Saliency Maps in Medical Imaging

* Machine Learning for Health (ML4H) at NeurIPS 2020 - Extended Abstract

Access Paper or Ask Questions

Federated Learning for Breast Density Classification: A Real-World Implementation

Sep 17, 2020
Holger R. Roth, Ken Chang, Praveer Singh, Nir Neumark, Wenqi Li, Vikash Gupta, Sharut Gupta, Liangqiong Qu, Alvin Ihsani, Bernardo C. Bizzo, Yuhong Wen, Varun Buch, Meesam Shah, Felipe Kitamura, Matheus Mendonça, Vitor Lavor, Ahmed Harouni, Colin Compas, Jesse Tetreault, Prerna Dogra, Yan Cheng, Selnur Erdal, Richard White, Behrooz Hashemian, Thomas Schultz, Miao Zhang, Adam McCarthy, B. Min Yun, Elshaimaa Sharaf, Katharina V. Hoebel, Jay B. Patel, Bryan Chen, Sean Ko, Evan Leibovitz, Etta D. Pisano, Laura Coombs, Daguang Xu, Keith J. Dreyer, Ittai Dayan, Ram C. Naidu, Mona Flores, Daniel Rubin, Jayashree Kalpathy-Cramer

Figure 2 for Federated Learning for Breast Density Classification: A Real-World Implementation

Figure 3 for Federated Learning for Breast Density Classification: A Real-World Implementation

Figure 4 for Federated Learning for Breast Density Classification: A Real-World Implementation

* Accepted at the 1st MICCAI Workshop on "Distributed And Collaborative Learning"; add citation to Fig. 1 & 2 and update Fig. 5

Access Paper or Ask Questions

Assessing the (Un)Trustworthiness of Saliency Maps for Localizing Abnormalities in Medical Imaging

Aug 06, 2020
Nishanth Arun, Nathan Gaw, Praveer Singh, Ken Chang, Mehak Aggarwal, Bryan Chen, Katharina Hoebel, Sharut Gupta, Jay Patel, Mishka Gidwani, Julius Adebayo, Matthew D. Li, Jayashree Kalpathy-Cramer

* Submitted to Nature Machine Intelligence. First four authors contributed equally to this work

Access Paper or Ask Questions