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06/19/2023
A Framework for Fast and Stable Representations of Multiparameter Persistent Homology Decompositions
Topological data analysis (TDA) is an area of data science that focuses ...
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06/06/2023
Stable Vectorization of Multiparameter Persistent Homology using Signed Barcodes as Measures
Persistent homology (PH) provides topological descriptors for geometric ...
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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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06/04/2022
Efficient Approximation of Multiparameter Persistence Modules
Topological Data Analysis is a growing area of data science, which aims ...
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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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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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06/14/2021
Topology identifies emerging adaptive mutations in SARS-CoV-2
The COVID-19 pandemic has lead to a worldwide effort to characterize its...
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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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10/16/2020
Optimizing persistent homology based functions
Solving optimization tasks based on functions and losses with a topologi...
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01/06/2020
MREC: a fast and versatile framework for aligning and matching point clouds with applications to single cell molecular data
Comparing and aligning large datasets is a pervasive problem occurring a...
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01/06/2020
MREC: a fast and versatile framework for aligning and matching data with applications to single cell molecular data
Comparing and aligning large datasets is a pervasive problem occurring a...
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12/23/2019
Approximation of Reeb spaces with Mappers and Applications to Stochastic Filters
Reeb spaces, as well as their discretized versions called Mappers, are c...
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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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12/04/2018
Topological Data Analysis of Single-cell Hi-C Contact Maps
In this article, we show how the recent statistical techniques developed...
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06/19/2018
On the Metric Distortion of Embedding Persistence Diagrams into separable Hilbert spaces
Persistence diagrams are important descriptors in Topological Data Analy...
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06/19/2018
On the Metric Distortion of Embedding Persistence Diagrams into Reproducing Kernel Hilbert Spaces
Persistence diagrams are important feature descriptors in Topological Da...
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06/11/2017
Sliced Wasserstein Kernel for Persistence Diagrams
Persistence diagrams (PDs) play a key role in topological data analysis ...
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06/01/2017
