38 citations · 110 across the 9 of their papers we have counts for
3 papers · 1 filter
Representational dissimilarity metric spaces for stochastic neural networks
Lyndon R. Duong, Jingyang Zhou, Josue Nassar +3
Quantifying similarity between neural representations -- e.g. hidden layer activation vectors -- is a perennial problem in deep learning and neuroscience research. Existing methods…
Fast Convolutive Nonnegative Matrix Factorization Through Coordinate and Block Coordinate Updates
Anthony Degleris, Ben Antin, Surya Ganguli +1
Identifying recurring patterns in high-dimensional time series data is an important problem in many scientific domains. A popular model to achieve this is convolutive nonnegative m…
Reverse engineering recurrent networks for sentiment classification reveals line attractor dynamics
Niru Maheswaranathan, Alex Williams, Matthew D. Golub +2
Recurrent neural networks (RNNs) are a widely used tool for modeling sequential data, yet they are often treated as inscrutable black boxes. Given a trained recurrent network, we w…