Search Results for author: Les Atlas

Found 6 papers, 4 papers with code

Estimating and Analyzing Neural Flow Using Signal Processing on Graphs

no code implementations27 May 2022 Felix Schwock, Les Atlas, Shima Abadi, Julien Bloch, Azadeh Yazdan-Shahmorad

Neural communication is fundamentally linked to the brain's overall state and health status.

Using a Novel COVID-19 Calculator to Measure Positive U.S. Socio-Economic Impact of a COVID-19 Pre-Screening Solution (AI/ML)

1 code implementation21 Jan 2022 Richard Swartzbaugh, Amil Khanzada, Praveen Govindan, Mert Pilanci, Ayomide Owoyemi, Les Atlas, Hugo Estrada, Richard Nall, Michael Lotito, Rich Falcone, Jennifer Ranjani J

The COVID-19 pandemic has been a scourge upon humanity, claiming the lives of more than 5. 1 million people worldwide; the global economy contracted by 3. 5% in 2020.

Deep Recurrent NMF for Speech Separation by Unfolding Iterative Thresholding

1 code implementation21 Sep 2017 Scott Wisdom, Thomas Powers, James Pitton, Les Atlas

This interpretability also provides principled initializations that enable faster training and convergence to better solutions compared to conventional random initialization.

Speech Separation

Interpretable Recurrent Neural Networks Using Sequential Sparse Recovery

1 code implementation22 Nov 2016 Scott Wisdom, Thomas Powers, James Pitton, Les Atlas

Recurrent neural networks (RNNs) are powerful and effective for processing sequential data.

Compressive Sensing

Full-Capacity Unitary Recurrent Neural Networks

2 code implementations NeurIPS 2016 Scott Wisdom, Thomas Powers, John R. Hershey, Jonathan Le Roux, Les Atlas

To address this question, we propose full-capacity uRNNs that optimize their recurrence matrix over all unitary matrices, leading to significantly improved performance over uRNNs that use a restricted-capacity recurrence matrix.

Sequential Image Classification

Enhancement and Recognition of Reverberant and Noisy Speech by Extending Its Coherence

no code implementations2 Sep 2015 Scott Wisdom, Thomas Powers, Les Atlas, James Pitton

Our approach centers around using a single-channel minimum mean-square error log-spectral amplitude (MMSE-LSA) estimator proposed by Habets, which scales coefficients in a time-frequency domain to suppress noise and reverberation.

Automatic Speech Recognition Speech Enhancement +1

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