15 citations · 53 across the 7 of their papers we have counts for
11 papers
Quantized Gromov-Wasserstein
Samir Chowdhury, David Miller, Tom Needham
The Gromov-Wasserstein (GW) framework adapts ideas from optimal transport to allow for the comparison of probability distributions defined on different metric spaces. Scalable comp…
Path homology and temporal networks
Samir Chowdhury, Steve Huntsman, Matvey Yutin
We present an algorithm to compute path homology for simple digraphs, and use it to topologically analyze various small digraphs en route to an analysis of complex temporal network…
Generalized Spectral Clustering via Gromov-Wasserstein Learning
Samir Chowdhury, Tom Needham
We establish a bridge between spectral clustering and Gromov-Wasserstein Learning (GWL), a recent optimal transport-based approach to graph partitioning. This connection both expla…
Path homologies of deep feedforward networks
Samir Chowdhury, Thomas Gebhart, Steve Huntsman +1
We provide a characterization of two types of directed homology for fully-connected, feedforward neural network architectures. These exact characterizations of the directed homolog…
Gromov-Wasserstein Averaging in a Riemannian Framework
Samir Chowdhury, Tom Needham
We introduce a theoretical framework for performing statistical tasks---including, but not limited to, averaging and principal component analysis---on the space of (possibly asymme…
Geodesics in persistence diagram space
Samir Chowdhury
It is known that for a variety of choices of metrics, including the standard bottleneck distance, the space of persistence diagrams admits geodesics. Typically these existence resu…
Vietoris-Rips Complexes of Regular Polygons
Henry Adams, Samir Chowdhury, Adam Quinn Jaffe +1
Persistent homology has emerged as a novel tool for data analysis in the past two decades. However, there are still very few shapes or even manifolds whose persistent homology barc…
New families of simplicial filtration functors
Samir Chowdhury, Nathaniel Clause, Facundo Memoli +2
The so called Čech and Vietoris-Rips simplicial filtrations are designed to capture information about the topological structure of metric datasets. These filtrations are two of the…
The Importance of Forgetting: Limiting Memory Improves Recovery of Topological Characteristics from Neural Data
Samir Chowdhury, Bowen Dai, Facundo Mémoli
We develop of a line of work initiated by Curto and Itskov towards understanding the amount of information contained in the spike trains of hippocampal place cells via topology con…
A functorial Dowker theorem and persistent homology of asymmetric networks
Samir Chowdhury, Facundo Mémoli
We study two methods for computing network features with topological underpinnings: the Rips and Dowker persistent homology diagrams. Our formulations work for general networks, wh…
Explicit Geodesics in Gromov-Hausdorff Space
Samir Chowdhury, Facundo Mémoli
We provide an alternative, constructive proof that the collection of isometry classes of compact metric spaces endowed with the Gromov-Hausdorff distance is a geodesi…