topf

_bibliography/papers.bib

@@ -3,6 +3,19 @@
 
 @string{aps = {American Physical Society,}}
 
+@misc{grande2024topf,
+  title         = {Node-Level Topological Representation Learning on Point Clouds},
+  author        = {Vincent P. Grande and Michael T. Schaub},
+  year          = {2024},
+  arxiv         = {2406.02300},
+  archiveprefix = {arXiv},
+  primaryclass  = {math.AT},
+  note          = {Arxiv preprint.},
+  selected      = {true},
+  preview       = {TOPFpreview.png},
+  code          = {https://github.com/vincent-grande/topf}
+}
+
 @article{grande2023topological,
   title         = {Topological Point Cloud Clustering},
   author        = {Vincent P. Grande and Michael T. Schaub},

_news/announcementTOPF.md

@@ -0,0 +1,8 @@
+---
+layout: post
+date: 2024-06-05 08:00:00+0100
+inline: true
+---
+
+A preprint to my new joint with [Michael Schaub](https://michaelschaub.github.io) paper ["Node-Level Topological Representation Learning on Point Clouds"](https://arxiv.org/abs/2406.02300) is now available on arxiv!
+We construct point-level features vectors quantifying the contribution of the points to the global shape and properties of the point cloud.

_news/announcementTOPFcode.md

@@ -0,0 +1,7 @@
+---
+layout: post
+date: 2024-06-06 08:00:00+0100
+inline: true
+---
+
+I have released my first python package `topf`, which computes topological point features in point clouds based on our [recent article](https://arxiv.org/abs/2406.02300). The code and  many examples are available [here](https://github.com/vincent-grande/topf) :blush:. Alternatively, install Julia and Python and simply run `pip install topf`. :potted_plant::tada:

_pages/code.md

@@ -7,6 +7,17 @@ nav: true
 nav_order: 3
 ---
 
+### Node-Level Topological Representation on Point Clouds :potted_plant:
+
+We provide a python package to compute node-level topological point features (TOPF) on point clouds.
+TOPF aims to capture the relationship between the point and the global topology of the point cloud.
+After installing `Julia`, you can install `topf` on Linux and macOS using
+
+    pip install topf
+
+[Code](https://github.com/vincent-grande/topf)
+[Paper](https://arxiv.org/abs/2406.02300)
+
 ### Disentangling the Spectral Properties of the Hodge Laplacian: Not All Small Eigenvalues Are Equal
 
 We provide many cool tools to leverage and analyse the spectral properties of a family of Hodge Laplacians defined on a filtration of simplicial complexes on a point cloud. The paper was accepted for publication at the 2024 IEEE Conference on Acoustics, Speech, And Signal Processing (ICASSP).