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09/15/2023
Topological Node2vec: Enhanced Graph Embedding via Persistent Homology
Node2vec is a graph embedding method that learns a vector representation...
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05/22/2023
MAGDiff: Covariate Data Set Shift Detection via Activation Graphs of Deep Neural Networks
Despite their successful application to a variety of tasks, neural netwo...
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02/03/2022
RipsNet: a general architecture for fast and robust estimation of the persistent homology of point clouds
The use of topological descriptors in modern machine learning applicatio...
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01/06/2022
An Homogeneous Unbalanced Regularized Optimal Transport model with applications to Optimal Transport with Boundary
This work studies how the introduction of the entropic regularization te...
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09/01/2021
A Gradient Sampling Algorithm for Stratified Maps with Applications to Topological Data Analysis
We introduce a novel gradient descent algorithm extending the well-known...
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05/11/2021
Estimation and Quantization of Expected Persistence Diagrams
Persistence diagrams (PDs) are the most common descriptors used to encod...
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05/07/2021
Topological Uncertainty: Monitoring trained neural networks through persistence of activation graphs
Although neural networks are capable of reaching astonishing performance...
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04/20/2019
PersLay: A Neural Network Layer for Persistence Diagrams and New Graph Topological Signatures
Persistence diagrams, the most common descriptors of Topological Data An...
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04/20/2019
PersLay: A Simple and Versatile Neural Network Layer for Persistence Diagrams
Persistence diagrams, a key descriptor from Topological Data Analysis, e...
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04/20/2019
A General Neural Network Architecture for Persistence Diagrams and Graph Classification
Graph classification is a difficult problem that has drawn a lot of atte...
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01/10/2019
Understanding the Topology and the Geometry of the Persistence Diagram Space via Optimal Partial Transport
We consider a generalization of persistence diagrams, namely Radon measu...
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05/22/2018
