Topological Data Analysis

123 papers with code • 0 benchmarks • 3 datasets

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Use these libraries to find Topological Data Analysis models and implementations

Most implemented papers

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.

Intrinsic Dimension, Persistent Homology and Generalization in Neural Networks

tolgabirdal/phdimgeneralization NeurIPS 2021

Disobeying the classical wisdom of statistical learning theory, modern deep neural networks generalize well even though they typically contain millions of parameters.

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.

Can BERT eat RuCoLA? Topological Data Analysis to Explain

upunaprosk/la-tda 4 Apr 2023

Our results contribute to understanding the behavior of monolingual LMs in the acceptability classification task, provide insights into the functional roles of attention heads, and highlight the advantages of TDA-based approaches for analyzing LMs.

Visualizing the Effects of a Changing Distance on Data Using Continuous Embeddings

ginagruenhage/cmdsr 8 Nov 2013

The right scale is hard to pin down and it is preferable when results do not depend too tightly on the exact value one picked.

A Riemannian Framework for Statistical Analysis of Topological Persistence Diagrams

rushilanirudh/pdsphere 28 May 2016

This paper concerns itself with one popular topological feature, which is the number of $d-$dimensional holes in the dataset, also known as the Betti$-d$ number.

Inference of Ancestral Recombination Graphs through Topological Data Analysis

RabadanLab/TARGet 27 Jul 2016

We build upon previous TDA developments for detecting and quantifying recombination, and present a novel framework that can be applied to hundreds of genomes and can be interpreted in terms of minimal histories of mutation and recombination events, quantifying the scales and identifying the genomic locations of recombinations.

Kernel method for persistence diagrams via kernel embedding and weight factor

genki-kusano/python-pwgk 12 Jun 2017

Topological data analysis is an emerging mathematical concept for characterizing shapes in multi-scale data.

An introduction to Topological Data Analysis: fundamental and practical aspects for data scientists

GUDHI/TDA-tutorial 11 Oct 2017

Topological Data Analysis is a recent and fast growing field providing a set of new topological and geometric tools to infer relevant features for possibly complex data.

Topological Data Analysis of Decision Boundaries with Application to Model Selection

nrkarthikeyan/topology-decision-boundaries 25 May 2018

We propose the labeled \v{C}ech complex, the plain labeled Vietoris-Rips complex, and the locally scaled labeled Vietoris-Rips complex to perform persistent homology inference of decision boundaries in classification tasks.