Bahareh Tolooshams

According to our database, Bahareh Tolooshams authored at least 22 papers between 2018 and 2025.

Collaborative distances:

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

2025

Ultrasound Lung Aeration Map via Physics-Aware Neural Operators.

Jiayun Wang, Oleksii Ostras, Masashi Sode, Bahareh Tolooshams, Zongyi Li, Kamyar Azizzadenesheli, Gianmarco Pinton, Anima Anandkumar

CoRR, January, 2025

2024

Unifying Subsampling Pattern Variations for Compressed Sensing MRI with Neural Operators.

Armeet Singh Jatyani, Jiayun Wang, Zihui Wu, Miguel Liu-Schiaffini, Bahareh Tolooshams, Anima Anandkumar

CoRR, 2024

Diffusion State-Guided Projected Gradient for Inverse Problems.

Rayhan Zirvi, Bahareh Tolooshams, Anima Anandkumar

CoRR, 2024

Fourier Neural Operators for Learning Dynamics in Quantum Spin Systems.

Freya Shah, Taylor L. Patti, Julius Berner, Bahareh Tolooshams, Jean Kossaifi, Anima Anandkumar

CoRR, 2024

2023

Unrolled Compressed Blind-Deconvolution.

Bahareh Tolooshams, Satish Mulleti, Demba E. Ba, Yonina C. Eldar

IEEE Trans. Signal Process., 2023

Probabilistic Unrolling: Scalable, Inverse-Free Maximum Likelihood Estimation for Latent Gaussian Models.

Alexander Lin, Bahareh Tolooshams, Yves F. Atchadé, Demba E. Ba

Proceedings of the International Conference on Machine Learning, 2023

2022

Stable and Interpretable Unrolled Dictionary Learning.

Bahareh Tolooshams, Demba E. Ba

Trans. Mach. Learn. Res., 2022

Gaussian Process Convolutional Dictionary Learning.

Andrew H. Song, Bahareh Tolooshams, Demba E. Ba

IEEE Signal Process. Lett., 2022

Learning Filter-Based Compressed Blind-Deconvolution.

Bahareh Tolooshams, Satish Mulleti, Demba E. Ba, Yonina C. Eldar

CoRR, 2022

A Training Framework for Stereo-Aware Speech Enhancement Using Deep Neural Networks.

Bahareh Tolooshams, Kazuhito Koishida

Proceedings of the IEEE International Conference on Acoustics, 2022

2021

Deep Residual Autoencoders for Expectation Maximization-Inspired Dictionary Learning.

Bahareh Tolooshams, Sourav Dey, Demba E. Ba

IEEE Trans. Neural Networks Learn. Syst., 2021

PUDLE: Implicit Acceleration of Dictionary Learning by Backpropagation.

Bahareh Tolooshams, Demba E. Ba

CoRR, 2021

On the convergence of group-sparse autoencoders.

Emmanouil Theodosis, Bahareh Tolooshams, Pranay Tankala, Abiy Tasissa, Demba E. Ba

CoRR, 2021

Unfolding Neural Networks for Compressive Multichannel Blind Deconvolution.

Bahareh Tolooshams, Satish Mulleti, Demba E. Ba, Yonina C. Eldar

Proceedings of the IEEE International Conference on Acoustics, 2021

2020

Dense and Sparse Coding: Theory and Architectures.

Abiy Tasissa, Emmanouil Theodosis, Bahareh Tolooshams, Demba E. Ba

CoRR, 2020

Convolutional dictionary learning based auto-encoders for natural exponential-family distributions.

Bahareh Tolooshams, Andrew H. Song, Simona Temereanca, Demba E. Ba

Proceedings of the 37th International Conference on Machine Learning, 2020

Channel-Attention Dense U-Net for Multichannel Speech Enhancement.

Bahareh Tolooshams, Ritwik Giri, Andrew H. Song, Umut Isik, Arvindh Krishnaswamy

Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

2019

Deep Exponential-Family Auto-Encoders.

Bahareh Tolooshams, Andrew H. Song, Simona Temereanca, Demba E. Ba

CoRR, 2019

Deep Residual Auto-Encoders for Expectation Maximization-based Dictionary Learning.

Bahareh Tolooshams, Sourav Dey, Demba E. Ba

CoRR, 2019

Randnet: Deep Learning with Compressed Measurements of Images.

Thomas Chang, Bahareh Tolooshams, Demba E. Ba

Proceedings of the 29th IEEE International Workshop on Machine Learning for Signal Processing, 2019

Convolutional Dictionary Learning in Hierarchical Networks.

Javier Zazo, Bahareh Tolooshams, Demba E. Ba

Proceedings of the 8th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2019

2018

Scalable Convolutional Dictionary Learning with constrained Recurrent Sparse Auto-encoders.

Bahareh Tolooshams, Sourav Dey, Demba E. Ba

Proceedings of the 28th IEEE International Workshop on Machine Learning for Signal Processing, 2018