
Approximation algorithms for 1Wasserstein distance between persistence diagrams
Recent years have witnessed a tremendous growth using topological summar...
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Equivariant geometric learning for digital rock physics: estimating formation factor and effective permeability tensors from Morse graph
We present a SE(3)equivariant graph neural network (GNN) approach that ...
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TopologyAware Segmentation Using Discrete Morse Theory
In the segmentation of finescale structures from natural and biomedical...
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Graph Coarsening with Neural Networks
As largescale graphs become increasingly more prevalent, it poses signi...
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Persistent Laplacians: properties, algorithms and implications
The combinatorial graph Laplacian has been a fundamental object in the a...
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Ordinally Consensus Subset over Multiple Metrics
In this paper, we propose to study the following maximum ordinal consens...
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A Note on OverSmoothing for Graph Neural Networks
Graph Neural Networks (GNNs) have achieved a lot of success on graphstr...
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Detection and skeletonization of single neurons and tracer injections using topological methods
Neuroscientific data analysis has traditionally relied on linear algebra...
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ElderRuleStaircodes for Augmented Metric Spaces
An augmented metric space is a metric space (X, d_X) equipped with a fun...
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An efficient algorithm for 1dimensional (persistent) path homology
This paper focuses on developing an efficient algorithm for analyzing a ...
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Understanding the Power of Persistence Pairing via Permutation Test
Recently many efforts have been made to incorporate persistence diagrams...
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A limit theorem for the 1st Betti number of layer1 subgraphs in random graphs
We initiate the study of local topology of random graphs. The high level...
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Road Network Reconstruction from Satellite Images with Machine Learning Supported by Topological Methods
Automatic Extraction of road network from satellite images is a goal tha...
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A Structural Average of Labeled Merge Trees for Uncertainty Visualization
Physical phenomena in science and engineering are frequently modeled usi...
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Intrinsic Interleaving Distance for Merge Trees
Merge trees are a type of graphbased topological summary that tracks th...
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Learning metrics for persistencebased summaries and applications for graph classification
Recently a new feature representation and data analysis methodology base...
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Local Versus Global Distances for Zigzag Persistence Modules
This short note establishes explicit and broadly applicable relationship...
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The Relationship Between the Intrinsic Cech and Persistence Distortion Distances for Metric Graphs
Metric graphs are meaningful objects for modeling complex structures tha...
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An Improved Cost Function for Hierarchical Cluster Trees
Hierarchical clustering has been a popular method in various data analys...
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A New Cost Function for Hierarchical Cluster Trees
Hierarchical clustering has been a popular method in various data analys...
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A simple yet effective baseline for nonattribute graph classification
Graphs are complex objects that do not lend themselves easily to typical...
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FPTalgorithms for computing GromovHausdorff and interleaving distances between trees
GromovHausdorff (GH) distance is a natural way to measure the distortio...
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Local cliques in ERperturbed random geometric graphs
Random graphs are mathematical models that have applications in a wide r...
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A Topological Regularizer for Classifiers via Persistent Homology
Regularization plays a crucial role in supervised learning. Most existin...
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TopoReg: A Topological Regularizer for Classifiers
Regularization plays a crucial role in supervised learning. A successful...
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Topological Skeletonization and TreeSummarization of Neurons Using Discrete Morse Theory
Neuroscientific data analysis has classically involved methods for stati...
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Graph Reconstruction by Discrete Morse Theory
Recovering hidden graphlike structures from potentially noisy data is a...
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Efficient algorithms for computing a minimal homology basis
Efficient computation of shortest cycles which form a homology basis und...
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VietorisRips and Cech Complexes of Metric Gluings
We study VietorisRips and Cech complexes of metric wedge sums and metri...
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Unperturbed: spectral analysis beyond DavisKahan
Classical matrix perturbation results, such as Weyl's theorem for eigenv...
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Graphons, mergeons, and so on!
In this work we develop a theory of hierarchical clustering for graphs. ...
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Beyond Hartigan Consistency: Merge Distortion Metric for Hierarchical Clustering
Hierarchical clustering is a popular method for analyzing data which ass...
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Graph Laplacians on Singular Manifolds: Toward understanding complex spaces: graph Laplacians on manifolds with singularities and boundaries
Recently, much of the existing work in manifold learning has been done u...
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Yusu Wang
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