4 citations · 5 across the 3 of their papers we have counts for
3 papers
Learning shared neural manifolds from multi-subject FMRI data
Jessie Huang, Erica L. Busch, Tom Wallenstein +6
Functional magnetic resonance imaging (fMRI) is a notoriously noisy measurement of brain activity because of the large variations between individuals, signals marred by environment…
Uncovering the Folding Landscape of RNA Secondary Structure with Deep Graph Embeddings
Egbert Castro, Andrew Benz, Alexander Tong +2
Biomolecular graph analysis has recently gained much attention in the emerging field of geometric deep learning. Here we focus on organizing biomolecular graphs in ways that expose…
Context-Free Transductions with Neural Stacks
Yiding Hao, William Merrill, Dana Angluin +4
This paper analyzes the behavior of stack-augmented recurrent neural network (RNN) models. Due to the architectural similarity between stack RNNs and pushdown transducers, we train…