blob: 906a9965f97e8c4eec3d3d1cee55f1648f80b0e7 (
plain)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
|
:orphan:
.. To get rid of WARNING: document isn't included in any toctree
======================
Differentiation manual
======================
.. include:: differentiation_sum.inc
In this module, we provide neural network models for computing persistent homology. In particular, we provide TensorFlow 2 models that allow to compute persistence diagrams from complexes available in the Gudhi library, including simplex trees, cubical complexes and Vietoris-Rips complexes. These models can be incorporated at each step of a given neural network architecture, and can be used in addition to `PersLay <https://github.com/MathieuCarriere/gudhi/blob/perslay/src/python/gudhi/representations/perslay.py>`_ to produce topological features.
TensorFlow models
-----------------
.. automodule:: gudhi.differentiation
:members:
:special-members:
:show-inheritance:
|
