Topological Data Analysis

96 papers with code • 0 benchmarks • 2 datasets

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Use these libraries to find Topological Data Analysis models and implementations

Most implemented papers

Persistence Images: A Stable Vector Representation of Persistent Homology

CSU-TDA/PersistenceImages 22 Jul 2015

We convert a PD to a finite-dimensional vector representation which we call a persistence image (PI), and prove the stability of this transformation with respect to small perturbations in the inputs.

Deep Learning with Topological Signatures

c-hofer/nips2017 NeurIPS 2017

Inferring topological and geometrical information from data can offer an alternative perspective on machine learning problems.

Mapper on Graphs for Network Visualization

USFDataVisualization/MapperOnGraphs 3 Apr 2018

We propose to apply the mapper construction--a popular tool in topological data analysis--to graph visualization, which provides a strong theoretical basis for summarizing network data while preserving their core structures.

Topological Autoencoders

BorgwardtLab/topological-autoencoders ICML 2020

We propose a novel approach for preserving topological structures of the input space in latent representations of autoencoders.

Scalable Topological Data Analysis and Visualization for Evaluating Data-Driven Models in Scientific Applications

rushilanirudh/icf-jag-cycleGAN 19 Jul 2019

With the rapid adoption of machine learning techniques for large-scale applications in science and engineering comes the convergence of two grand challenges in visualization.

Mapper Based Classifier

asgeorges/mapper-classifier 17 Oct 2019

We propose a classifier based on applying the Mapper algorithm to data projected onto a latent space.

Markov-Lipschitz Deep Learning

westlake-cairi/Markov-Lipschitz-Deep-Learning 15 Jun 2020

We propose a novel framework, called Markov-Lipschitz deep learning (MLDL), to tackle geometric deterioration caused by collapse, twisting, or crossing in vector-based neural network transformations for manifold-based representation learning and manifold data generation.

Particle gradient descent model for point process generation

abrochar/pp_syn 27 Oct 2020

This paper presents a statistical model for stationary ergodic point processes, estimated from a single realization observed in a square window.

Artificial Text Detection via Examining the Topology of Attention Maps

danchern97/tda4atd EMNLP 2021

The impressive capabilities of recent generative models to create texts that are challenging to distinguish from the human-written ones can be misused for generating fake news, product reviews, and even abusive content.

Multiscale topology classifies and quantifies cell types in subcellular spatial transcriptomics

katherine-benjamin/topact-paper 13 Dec 2022

Spatial transcriptomics has the potential to transform our understanding of RNA expression in tissues.