This is an implementation of the algorithms from the paper https://arxiv.org/pdf/2201.00058
Barannikov, S., Trofimov, I., Balabin, N., & Burnaev, E. (2022).
Representation Topology Divergence: A Method for Comparing Neural Network Representations. ICML'22.
Example.ipynb can be executed in Google Colab.
- Requires numpy, scipy, torch.
- Install ripserplusplus:
pip install git+https://github.com/simonzhang00/ripser-plusplus.git - Install RTD:
pip install git+https://github.com/IlyaTrofimov/RTD.git
Alternatively, you can use dockerfile.
In the docker, run conda activate py37 after start. The directory RTD/experiments contains jupyter notebooks with experiments from the paper.
import numpy as np
import rtd
np.random.seed(7)
P = np.random.rand(1000, 2)
Q = np.random.rand(1000, 2)
barc = rtd.calc_embed_dist(P, Q)
rtd.plot_barcodes(rtd.barc2array(barc))rtd.rtd(P, Q)
35.55234398557805