2 citations · 3 across the 3 of their papers we have counts for
4 papers
Quasi Monte Carlo methods enable extremely low-dimensional deep generative models
Miles Martinez, Alex H. Williams
This paper introduces quasi-Monte Carlo latent variable models (QLVMs): a class of deep generative models that are specialized for finding extremely low-dimensional and interpretab…
Modeling Neural Activity with Conditionally Linear Dynamical Systems
Victor Geadah, Amin Nejatbakhsh, David Lipshutz +2
Neural population activity exhibits complex, nonlinear dynamics, varying in time, over trials, and across experimental conditions. Here, we develop Conditionally Linear Dynamical S…
Comparing noisy neural population dynamics using optimal transport distances
Amin Nejatbakhsh, Victor Geadah, Alex H. Williams +1
Biological and artificial neural systems form high-dimensional neural representations that underpin their computational capabilities. Methods for quantifying geometric similarity i…
What Representational Similarity Measures Imply about Decodable Information
Sarah E. Harvey, David Lipshutz, Alex H. Williams
Neural responses encode information that is useful for a variety of downstream tasks. A common approach to understand these systems is to build regression models or ``decoders'' th…