Bahareh Tolooshams
Title
Cited by
Cited by
Year
Scalable convolutional dictionary learning with constrained recurrent sparse auto-encoders
B Tolooshams, S Dey, D Ba
IEEE 28th International Workshop on Machine Learning for Signal Processing …, 2018
142018
Channel-attention dense u-net for multichannel speech enhancement
B Tolooshams, R Giri, AH Song, U Isik, A Krishnaswamy
IEEE 45th International Conference on Acoustics, Speech, and Signal …, 2020
112020
Robustness of frequency division technique for online myoelectric pattern recognition against contraction level variation
B Tolooshams, N Jiang
Frontiers in bioengineering and biotechnology 5, 3, 2017
112017
Deep residual autoencoders for expectation maximization-inspired dictionary learning
B Tolooshams, S Dey, D Ba
IEEE Transactions on Neural Networks and Learning Systems, 2020
62020
RandNet: deep learning with compressed measurements of images
T Chang, B Tolooshams, D Ba
IEEE 29th International Workshop on Machine Learning for Signal Processing …, 2019
52019
Convolutional dictionary learning based auto-encoders for natural exponential-family distributions
B Tolooshams, AH Song, S Temereanca, D Ba
Proceedings of the 37th International Conference on Machine Learning, 2020
32020
Convolutional dictionary learning in hierarchical networks
J Zazo, B Tolooshams, D Ba
IEEE 8th International Workshop on Computational Advances in Multi-Sensor …, 2019
22019
On the convergence of group-sparse autoencoders
E Theodosis, B Tolooshams, P Tankala, A Tasissa, D Ba
arXiv preprint arXiv:2102.07003, 2021
2021
Unsupervised learning of a dictionary of neural impulse responses from spiking data
B Tolooshams, H Wu, P Masset, VN Murthy, D Ba
Computational and Systems Neuroscience, 2021
2021
Unfolding neural networks for compressive multichannel blind deconvolution
B Tolooshams, S Mulleti, D Ba, YC Eldar
arXiv preprint arXiv:2010.11391, 2020
2020
Dense and sparse coding: theory and architectures
A Tasissa, E Theodosis, B Tolooshams, D Ba
arXiv preprint arXiv:2006.09534, 2020
2020
Convolutional dictionary learning of stimulus from spiking data
AH Song, B Tolooshams, S Temereanca, D Ba
Computational and Systems Neuroscience, 2020
2020
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Articles 1–12