From 51a0ed4b402b7fdc0cf532515dbabb34085d46ce Mon Sep 17 00:00:00 2001 From: Caleb Geniesse Date: Tue, 16 Aug 2022 16:50:26 -0700 Subject: [PATCH] Update README.md --- README.md | 20 ++++++++++---------- 1 file changed, 10 insertions(+), 10 deletions(-) diff --git a/README.md b/README.md index 96a62f1..ab90780 100644 --- a/README.md +++ b/README.md @@ -17,6 +17,16 @@ For more details about NeuMapper see "[NeuMapper: A Scalable Computational Frame +## **Related Projects** + +- [Reciprocal Isomap](https://calebgeniesse.github.io/reciprocal_isomap) is a reciprocal variant of Isomap for robust non-linear dimensionality reduction in Python. `ReciprocalIsomap` was inspired by scikit-learn's implementation of Isomap, but the reciprocal variant enforces shared connectivity in the underlying *k*-nearest neighbors graph (i.e., two points are only considered neighbors if each is a neighbor of the other). + +- [Landmark Cover](https://calebgeniesse.github.io/landmark_cover) is a landmark-based cover for Mapper. `LandmarkCover` was designed for use with [KeplerMapper](https://kepler-mapper.scikit-tda.org/en/latest/), but rather than dividing an *extrinsic* space (e.g., low-dimensional projection) into overlapping hypercubes, the landmark-based approach directly partitions data points into overlapping subsets based on their *intrinsic* distances from pre-selected landmark points. + +- [DyNeuSR](https://braindynamicslab.github.io/dyneusr/) is a Python library for visualizing topological representations of neuroimaging data. The package combines visual web components with a high-level Python interface for interacting with, manipulating, and visualizing topological graph representations of functional brain activity. + + + ## **Setup** ### **Dependencies** @@ -220,16 +230,6 @@ dG.visualize('haxby_decoding_neumapper_dyneusr.html') -## **Related Projects** - -- [DyNeuSR](https://braindynamicslab.github.io/dyneusr/) is a Python library for visualizing topological representations of neuroimaging data. The package combines visual web components with a high-level Python interface for interacting with, manipulating, and visualizing topological graph representations of functional brain activity. - -- [Reciprocal Isomap](https://calebgeniesse.github.io/reciprocal_isomap) is a reciprocal variant of Isomap for robust non-linear dimensionality reduction in Python. `ReciprocalIsomap` was inspired by scikit-learn's implementation of Isomap, but the reciprocal variant enforces shared connectivity in the underlying *k*-nearest neighbors graph (i.e., two points are only considered neighbors if each is a neighbor of the other). - -- [Landmark Cover](https://calebgeniesse.github.io/landmark_cover) is a landmark-based cover for Mapper. `LandmarkCover` was designed for use with [KeplerMapper](https://kepler-mapper.scikit-tda.org/en/latest/), but rather than dividing an *extrinsic* space (e.g., low-dimensional projection) into overlapping hypercubes, the landmark-based approach directly partitions data points into overlapping subsets based on their *intrinsic* distances from pre-selected landmark points. - - - ## **References** If you find NeuMapper useful, please consider citing: