On the public citation graph
On the Application of Topological Data Analysis and Machine Learning to Flood Incidents, and Decision Making
0 signed · 26 inferred · view as graph
Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.
Is this your work? Sign in with ORCID and put your name on the
claims that are yours.
Reference health. See whether every reference in this work resolves to a
known work and none has been retracted — and get a dated CiteStamped
badge you can embed.
What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/978-3-319-30265-2_7openalex-extracted
Topology, Big Data and Optimization
inferredcites →https://doi.org/10.1016/j.eswa.2015.04.010openalex-extracted
Persistent homology for time series and spatial data clustering
inferredcites →https://doi.org/10.1016/j.flowmeasinst.2021.102084openalex-extracted
Two-phase flow pattern classification based on void fraction time series and machine learning
inferredcites →https://doi.org/10.1016/j.gsf.2020.09.006openalex-extracted
Flood susceptibility modelling using advanced ensemble machine learning models
inferredcites →https://doi.org/10.1016/j.ins.2021.10.047openalex-extracted
A pattern-aware self-attention network for distant supervised relation extraction
inferredcites →https://doi.org/10.1016/j.ins.2021.10.055openalex-extracted
LGCNet: A local-to-global context-aware feature augmentation network for salient object detection
inferredcites →https://doi.org/10.1016/j.jmsy.2017.02.015openalex-extracted
Identification of key features using topological data analysis for accurate prediction of manufacturing system outputs
inferredcites →https://doi.org/10.1017/s0004972700028574openalex-extracted
A distance for similarity classes of submanifolds of a Euclidean space
inferredcites →https://doi.org/10.1080/10618600.2019.1573686openalex-extracted
The Accumulated Persistence Function, a New Useful Functional Summary Statistic for Topological Data Analysis, With a View to Brain Artery Trees and Spatial Point Process Applications
inferredcites →https://doi.org/10.1088/1742-6596/439/1/012042openalex-extracted
Hyperspectral image classification using Support Vector Machine
inferredcites →https://doi.org/10.1103/physrevresearch.2.033426openalex-extracted
Spatial applications of topological data analysis: Cities, snowflakes, random structures, and spiders spinning under the influence
inferredcites →https://doi.org/10.1103/physrevresearch.3.029003openalex-extracted
Erratum: Spatial applications of topological data analysis: Cities, snowflakes, random structures, and spiders spinning under the influence [Phys. Rev. Research 2 , 033426 (2020)]
inferredcites →https://doi.org/10.1111/1467-9868.00293openalex-extracted
Estimating the Number of Clusters in a Data Set Via the Gap Statistic
inferredcites →https://doi.org/10.18653/v1/d15-1203openalex-extracted
Distant Supervision for Relation Extraction via Piecewise Convolutional Neural Networks
inferredcites →https://doi.org/10.21203/rs.3.rs-459258/v1openalex-extracted
On the Cluster Validity Test (s) in Unsupervised Machine Learning TDA Approach for Atmospheric River Patterns on Flood Detection in Nigeria
inferredcites →https://doi.org/10.2991/assehr.k.200306.069openalex-extracted
Topological Methods for the Analysis of Applications
inferredcites →https://doi.org/10.48550/arxiv.1207.6437openalex-extracted
Statistical topological data analysis using persistence landscapes
inferredcites →https://doi.org/10.48550/arxiv.1804.06987openalex-extracted
Improving Distantly Supervised Relation Extraction using Word and Entity Based Attention
inferredcites →https://doi.org/10.48550/arxiv.1809.10745openalex-extracted
A Short Survey of Topological Data Analysis in Time Series and Systems Analysis
inferredcites →https://doi.org/10.48550/arxiv.1906.01507openalex-extracted
A numerical measure of the instability of Mapper-type algorithms
inferredcites →https://doi.org/10.5555/2789272.2789275openalex-extracted
Statistical topological data analysis using persistence landscapes
inferredcites →https://doi.org/10.5860/choice.46-3313openalex-extracted
Euler's gem: the polyhedron formula and the birth of topology
inferredcites →https://doi.org/10.6084/m9.figshare.7728554openalex-extracted
The Accumulated Persistence Function, a New Useful Functional Summary Statistic for Topological Data Analysis, With a View to Brain Artery Trees and Spatial Point Process Applications
inferredcites →https://doi.org/10.1186/s12859-020-03659-3openalex-snapshot
A topological data analysis based classification method for multiple measurements
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1007/s00542-025-05859-4openalex-snapshot
The synergy of topological data analysis and machine learning for low-cost e-nose systems
Editorial review for independent work. ICSAC — the Institute for Complexity
Science and Advanced Computing — runs a structured editorial panel for researchers
publishing outside journals, and publishes on CiteStamp rails. Submission is free
and goes through ORCID: icsacinstitute.org/submit.