44 citations · 253 across the 39 of their papers we have counts for
4 papers · 1 filter
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…
Molecular Graph Generation via Geometric Scattering
Dhananjay Bhaskar, Jackson D. Grady, Michael A. Perlmutter +1
Graph neural networks (GNNs) have been used extensively for addressing problems in drug design and discovery. Both ligand and target molecules are represented as graphs with node a…
Diffusion Earth Mover's Distance and Distribution Embeddings
Alexander Tong, Guillaume Huguet, Amine Natik +5
We propose a new fast method of measuring distances between large numbers of related high dimensional datasets called the Diffusion Earth Mover's Distance (EMD). We model the datas…
Exploring the Geometry and Topology of Neural Network Loss Landscapes
Stefan Horoi, Jessie Huang, Bastian Rieck +3
Recent work has established clear links between the generalization performance of trained neural networks and the geometry of their loss landscape near the local minima to which th…