Joseph Antognini

I am a Google AI Resident. Prior to my work at Google I worked in astronomy studying the dynamics of few-body systems. My current research interests are threefold: 1. Applying deep learning to the audio domain. In particular I am interested in the problem of fast spectrogram inversion. 2. Understanding the training dynamics of neural networks. 3. Applying deep learning to problems in astronomy.

Research Areas

Authored Publications
0 results

Sort By
  • Title
  • Title, descending
  • Year
  • Year, descending
    Google
Audio Texture Synthesis with Random Neural Networks: Improving Diversity and Quality
Joseph Antognini
Matthew D. Hoffman
Ron J. Weiss
ICASSP (2019)
Measuring the Effects of Data Parallelism on Neural Network Training
Chris Shallue
Jaehoon Lee
Joseph Antognini
Jascha Sohl-dickstein
Roy Frostig
George Dahl
Journal of Machine Learning Research (JMLR) (2018)
PCA of high dimensional random walks with comparison to neural network training
Joseph Antognini
Jascha Sohl-Dickstein
NeurIPS (2018)
Search on Google Scholar