1 citations · 1 across the 1 of their papers we have counts for
7 papers
Finite size corrections for neural network Gaussian processes
Joseph M. Antognini
There has been a recent surge of interest in modeling neural networks (NNs) as Gaussian processes. In the limit of a NN of infinite width the NN becomes equivalent to a Gaussian pr…
WHAM!: Extending Speech Separation to Noisy Environments
Gordon Wichern, Joe Antognini, Michael Flynn +5
Recent progress in separating the speech signals from multiple overlapping speakers using a single audio channel has brought us closer to solving the cocktail party problem. Howeve…
Measuring the Effects of Data Parallelism on Neural Network Training
Christopher J. Shallue, Jaehoon Lee, Joseph Antognini +3
Recent hardware developments have dramatically increased the scale of data parallelism available for neural network training. Among the simplest ways to harness next-generation har…
Velocity-resolved reverberation mapping of five bright Seyfert 1 galaxies
G. De Rosa, M. M. Fausnaugh, C. J. Grier +99
We present the first results from a reverberation-mapping campaign undertaken during the first half of 2012, with additional data on one AGN (NGC 3227) from a 2014 campaign. Our ma…
PCA of high dimensional random walks with comparison to neural network training
Joseph M. Antognini, Jascha Sohl-Dickstein
One technique to visualize the training of neural networks is to perform PCA on the parameters over the course of training and to project to the subspace spanned by the first few P…
Synthesizing Diverse, High-Quality Audio Textures
Joseph Antognini, Matt Hoffman, Ron J. Weiss
Texture synthesis techniques based on matching the Gram matrix of feature activations in neural networks have achieved spectacular success in the image domain. In this paper we ext…