111 citations · 149 across the 4 of their papers we have counts for
4 papers
Complex Clipping for Improved Generalization in Machine Learning
Les Atlas, Nicholas Rasmussen, Felix Schwock +1
For many machine learning applications, a common input representation is a spectrogram. The underlying representation for a spectrogram is a short time Fourier transform (STFT) whi…
Using a Novel COVID-19 Calculator to Measure Positive U.S. Socio-Economic Impact of a COVID-19 Pre-Screening Solution (AI/ML)
Richard Swartzbaugh, Amil Khanzada, Praveen Govindan +8
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. This paper pres…
Interpretable Recurrent Neural Networks Using Sequential Sparse Recovery
Scott Wisdom, Thomas Powers, James Pitton +1
Recurrent neural networks (RNNs) are powerful and effective for processing sequential data. However, RNNs are usually considered "black box" models whose internal structure and lea…
Full-Capacity Unitary Recurrent Neural Networks
Scott Wisdom, Thomas Powers, John R. Hershey +2
Recurrent neural networks are powerful models for processing sequential data, but they are generally plagued by vanishing and exploding gradient problems. Unitary recurrent neural…