Arjun D. Desai

According to our database, Arjun D. Desai authored at least 15 papers between 2019 and 2024.

Collaborative distances:

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

2024

Prospector Heads: Generalized Feature Attribution for Large Models & Data.

Gautam Machiraju, Alexander Derry, Arjun D. Desai, Neel Guha, Amir-Hossein Karimi, James Zou, Russ B. Altman, Christopher Ré, Parag Mallick

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Model ChangeLists: Characterizing Updates to ML Models.

Sabri Eyuboglu, Karan Goel, Arjun D. Desai, Lingjiao Chen, Mathew Monfort, Christopher Ré, James Zou

Proceedings of the 2024 ACM Conference on Fairness, Accountability, and Transparency, 2024

2023

Comp2Comp: Open-Source Body Composition Assessment on Computed Tomography.

Louis Blankemeier, Arjun D. Desai, Juan Manuel Zambrano Chaves, Andrew Wentland, Sally Yao, Eduardo Pontes Reis, Malte E. K. Jensen, Bhanushree Bahl, Khushboo Arora, Bhavik N. Patel, Leon Lenchik, Marc H. Willis, Robert D. Boutin, Akshay S. Chaudhari

CoRR, 2023

Deep Anatomical Federated Network (Dafne): an open client/server framework for the continuous collaborative improvement of deep-learning-based medical image segmentation.

Francesco Santini, Jakob Wasserthal, Abramo Agosti, Xeni Deligianni, Kevin R. Keene, Hermien E. Kan, Stefan Sommer, Christoph Stuprich, Fengdan Wang, Claudia Weidensteiner, Giulia Manco, Matteo Paoletti, Valentina Mazzoli, Arjun D. Desai, Anna Pichiecchio

CoRR, 2023

2022

Scale-Agnostic Super-Resolution in MRI using Feature-Based Coordinate Networks.

Dave Van Veen, Rogier van der Sluijs, Batu Ozturkler, Arjun D. Desai, Christian Bluethgen, Robert D. Boutin, Marc H. Willis, Gordon Wetzstein, David B. Lindell, Shreyas Vasanawala, John M. Pauly, Akshay S. Chaudhari

CoRR, 2022

Data-Limited Tissue Segmentation using Inpainting-Based Self-Supervised Learning.

Jeffrey Dominic, Nandita Bhaskhar, Arjun D. Desai, Andrew M. Schmidt, Elka B. Rubin, Beliz Gunel, Garry E. Gold, Brian A. Hargreaves, Leon Lenchik, Robert Boutin, Akshay S. Chaudhari

CoRR, 2022

GLEAM: Greedy Learning for Large-Scale Accelerated MRI Reconstruction.

Batu Ozturkler, Arda Sahiner, Tolga Ergen, Arjun D. Desai, Christopher M. Sandino, Shreyas Vasanawala, John M. Pauly, Morteza Mardani, Mert Pilanci

CoRR, 2022

VORTEX: Physics-Driven Data Augmentations Using Consistency Training for Robust Accelerated MRI Reconstruction.

Arjun D. Desai, Beliz Gunel, Batu M. Ozturkler, Harris Beg, Shreyas Vasanawala, Brian A. Hargreaves, Christopher Ré, John M. Pauly, Akshay S. Chaudhari

Proceedings of the International Conference on Medical Imaging with Deep Learning, 2022

Scale-Equivariant Unrolled Neural Networks for Data-Efficient Accelerated MRI Reconstruction.

Beliz Gunel, Arda Sahiner, Arjun D. Desai, Akshay S. Chaudhari, Shreyas Vasanawala, Mert Pilanci, John M. Pauly

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2022, 2022

Monarch: Expressive Structured Matrices for Efficient and Accurate Training.

Tri Dao, Beidi Chen, Nimit Sharad Sohoni, Arjun D. Desai, Michael Poli, Jessica Grogan, Alexander Liu, Aniruddh Rao, Atri Rudra, Christopher Ré

Proceedings of the International Conference on Machine Learning, 2022

2021

Noise2Recon: A Semi-Supervised Framework for Joint MRI Reconstruction and Denoising.

Arjun D. Desai, Batu M. Ozturkler, Christopher M. Sandino, Shreyas Vasanawala, Brian A. Hargreaves, Christopher Ré, John M. Pauly, Akshay S. Chaudhari

CoRR, 2021

SKM-TEA: A Dataset for Accelerated MRI Reconstruction with Dense Image Labels for Quantitative Clinical Evaluation.

Arjun D. Desai, Andrew M. Schmidt, Elka B. Rubin, Christopher M. Sandino, Marianne S. Black, Valentina Mazzoli, Kathryn J. Stevens, Robert Boutin, Christopher Ré, Garry Gold, Brian A. Hargreaves, Akshay Chaudhari

Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021

2020

The International Workshop on Osteoarthritis Imaging Knee MRI Segmentation Challenge: A Multi-Institute Evaluation and Analysis Framework on a Standardized Dataset.

Arjun D. Desai, Francesco Calivá, Claudia Iriondo, Naji Khosravan, Aliasghar Mortazi, Sachin Jambawalikar, Drew A. Torigian, Jutta Ellermann, Mehmet Akçakaya, Ulas Bagci, Radhika Tibrewala, Io Flament, Matthew O'Brien, Sharmila Majumdar, Mathias Perslev, Akshay Pai, Christian Igel, Erik B. Dam, Sibaji Gaj, Mingrui Yang, Kunio Nakamura, Xiaojuan Li, Cem M. Deniz, Vladimir Juras, Ravinder Regatte, Garry Gold, Brian A. Hargreaves, Valentina Pedoia, Akshay S. Chaudhari

CoRR, 2020

Using Computer Vision to Automate Hand Detection and Tracking of Surgeon Movements in Videos of Open Surgery.

Michael Zhang, Xiaotian Cheng, Daniel Copeland, Arjun D. Desai, Melody Y. Guan, Gabriel A. Brat, Serena Yeung

Proceedings of the AMIA 2020, 2020

2019

Technical Considerations for Semantic Segmentation in MRI using Convolutional Neural Networks.

Arjun D. Desai, Garry Gold, Brian A. Hargreaves, Akshay Chaudhari

CoRR, 2019