Sanketh Vedula

According to our database, Sanketh Vedula authored at least 20 papers between 2017 and 2024.

Collaborative distances:

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

2024

Scalable unsupervised alignment of general metric and non-metric structures.

Sanketh Vedula, Valentino Maiorca, Lorenzo Basile, Francesco Locatello, Alexander M. Bronstein

CoRR, 2024

Vector Quantile Regression on Manifolds.

Marco Pegoraro, Sanketh Vedula, Aviv Rosenberg, Irene Tallini, Emanuele Rodolà, Alex M. Bronstein

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023

Demystifying Graph Sparsification Algorithms in Graph Properties Preservation.

Yuhan Chen, Haojie Ye, Sanketh Vedula, Alex M. Bronstein, Ronald G. Dreslinski, Trevor N. Mudge, Nishil Talati

Proc. VLDB Endow., November, 2023

Everest: GPU-Accelerated System For Mining Temporal Motifs.

Yichao Yuan, Haojie Ye, Sanketh Vedula, Wynn Kaza, Nishil Talati

Proc. VLDB Endow., 2023

Fast Nonlinear Vector Quantile Regression.

Aviv A. Rosenberg, Sanketh Vedula, Yaniv Romano, Alexander M. Bronstein

Proceedings of the Eleventh International Conference on Learning Representations, 2023

GRACE: A Scalable Graph-Based Approach to Accelerating Recommendation Model Inference.

Haojie Ye, Sanketh Vedula, Yuhan Chen, Yichen Yang, Alex M. Bronstein, Ronald G. Dreslinski, Trevor N. Mudge, Nishil Talati

Proceedings of the 28th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, 2023

2022

Mint: An Accelerator For Mining Temporal Motifs.

Nishil Talati, Haojie Ye, Sanketh Vedula, Kuan-Yu Chen, Yuhan Chen, Daniel Liu, Yichao Yuan, David T. Blaauw, Alex M. Bronstein, Trevor N. Mudge, Ronald G. Dreslinski

Proceedings of the 55th IEEE/ACM International Symposium on Microarchitecture, 2022

2021

Spectral Geometric Matrix Completion.

Amit Boyarski, Sanketh Vedula, Alexander M. Bronstein

Proceedings of the Mathematical and Scientific Machine Learning, 2021

Joint Optimization of System Design and Reconstruction in MIMO Radar Imaging.

Tomer Weiss, Nissim Peretz, Sanketh Vedula, Arie Feuer, Alexander M. Bronstein

Proceedings of the 2021 IEEE 31st International Workshop on Machine Learning for Signal Processing (MLSP), 2021

2020

Towards learned optimal q-space sampling in diffusion MRI.

Tomer Weiss, Sanketh Vedula, Ortal Senouf, Oleg V. Michailovich, Alex M. Bronstein

CoRR, 2020

3D FLAT: Feasible Learned Acquisition Trajectories for Accelerated MRI.

Jonathan Alush-Aben, Linor Ackerman-Schraier, Tomer Weiss, Sanketh Vedula, Ortal Senouf, Alex M. Bronstein

Proceedings of the Machine Learning for Medical Image Reconstruction, 2020

Joint Learning of Cartesian under Sampling Andre Construction for Accelerated MRI.

Tomer Weiss, Sanketh Vedula, Ortal Senouf, Oleg V. Michailovich, Michael Zibulevsky, Alexander M. Bronstein

Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

2019

Deep geometric matrix completion: Are we doing it right?

Amit Boyarski, Sanketh Vedula, Alex M. Bronstein

CoRR, 2019

PILOT: Physics-Informed Learned Optimal Trajectories for Accelerated MRI.

Tomer Weiss, Ortal Senouf, Sanketh Vedula, Oleg V. Michailovich, Michael Zibulevsky, Alexander M. Bronstein

CoRR, 2019

Learning Fast Magnetic Resonance Imaging.

Tomer Weiss, Sanketh Vedula, Ortal Senouf, Alexander M. Bronstein, Oleg V. Michailovich, Michael Zibulevsky

CoRR, 2019

Learning beamforming in ultrasound imaging.

Sanketh Vedula, Ortal Senouf, Grigoriy Zurakhov, Alexander M. Bronstein, Oleg V. Michailovich, Michael Zibulevsky

Proceedings of the International Conference on Medical Imaging with Deep Learning, 2019

Self-supervised Learning of Inverse Problem Solvers in Medical Imaging.

Ortal Senouf, Sanketh Vedula, Tomer Weiss, Alexander M. Bronstein, Oleg V. Michailovich, Michael Zibulevsky

Proceedings of the Domain Adaptation and Representation Transfer and Medical Image Learning with Less Labels and Imperfect Data, 2019

2018

High Quality Ultrasonic Multi-line Transmission Through Deep Learning.

Sanketh Vedula, Ortal Senouf, Grigoriy Zurakhov, Alexander M. Bronstein, Michael Zibulevsky, Oleg V. Michailovich, Dan Adam, Diana Gaitini

Proceedings of the Machine Learning for Medical Image Reconstruction, 2018

High Frame-Rate Cardiac Ultrasound Imaging with Deep Learning.

Ortal Senouf, Sanketh Vedula, Grigoriy Zurakhov, Alexander M. Bronstein, Michael Zibulevsky, Oleg V. Michailovich, Dan Adam, David Blondheim

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2018, 2018

2017

Towards CT-quality Ultrasound Imaging using Deep Learning.

Sanketh Vedula, Ortal Senouf, Alexander M. Bronstein, Oleg V. Michailovich, Michael Zibulevsky

CoRR, 2017