82 citations · 98 across the 6 of their papers we have counts for
6 papers
Flow Factorized Representation Learning
Yue Song, T. Anderson Keller, Nicu Sebe +1
A prominent goal of representation learning research is to achieve representations which are factorized in a useful manner with respect to the ground truth factors of variation. Th…
Traveling Waves Encode the Recent Past and Enhance Sequence Learning
T. Anderson Keller, Lyle Muller, Terrence Sejnowski +1
Traveling waves of neural activity have been observed throughout the brain at a diversity of regions and scales; however, their precise computational role is still debated. One phy…
DUET: 2D Structured and Approximately Equivariant Representations
Xavier Suau, Federico Danieli, T. Anderson Keller +5
Multiview Self-Supervised Learning (MSSL) is based on learning invariances with respect to a set of input transformations. However, invariance partially or totally removes transfor…
Homomorphic Self-Supervised Learning
T. Anderson Keller, Xavier Suau, Luca Zappella
In this work, we observe that many existing self-supervised learning algorithms can be both unified and generalized when seen through the lens of equivariant representations. Speci…
Topographic VAEs learn Equivariant Capsules
T. Anderson Keller, Max Welling
In this work we seek to bridge the concepts of topographic organization and equivariance in neural networks. To accomplish this, we introduce the Topographic VAE: a novel method fo…
Experimental Realization of a Nonlinear Acoustic Lens with a Tunable Focus
Carly M. Donahue, Paul W. J. Anzel, Luca Bonanomi +2
We realize a nonlinear acoustic lens composed of a two-dimensional array of sphere chains interfaced with water. The chains are able to support solitary waves which, when interface…