3.6k citations · 6.2k across the 27 of their papers we have counts for
4 papers · 1 filter
Towards Learning Universal Audio Representations
Luyu Wang, Pauline Luc, Yan Wu +8
The ability to learn universal audio representations that can solve diverse speech, music, and environment tasks can spur many applications that require general sound content under…
Variable-rate discrete representation learning
Sander Dieleman, Charlie Nash, Jesse Engel +1
Semantically meaningful information content in perceptual signals is usually unevenly distributed. In speech signals for example, there are often many silences, and the speed of pr…
Generating Images with Sparse Representations
Charlie Nash, Jacob Menick, Sander Dieleman +1
The high dimensionality of images presents architecture and sampling-efficiency challenges for likelihood-based generative models. Previous approaches such as VQ-VAE use deep autoe…
A Deep Learning Approach for Characterizing Major Galaxy Mergers
Skanda Koppula, Victor Bapst, Marc Huertas-Company +15
Fine-grained estimation of galaxy merger stages from observations is a key problem useful for validation of our current theoretical understanding of galaxy formation. To this end,…