Hyperbolic Procrustes Analysis Using Riemannian Geometry

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Deep Learning HyperbolicProcrustesAnalysis
Overview

Hyperbolic Procrustes Analysis Using Riemannian Geometry

The code in this repository creates the figures presented in this article: Please notice that in order to apply the code to the data sets, they need to be downloaded first from the following specified links. The code was developed and tested in Python 3.8.

Demo - Simulations

The script 'Main.py' generates the discrepancies of baseline, HPA, and RT for the simulated examples, reported in Figure 2.

Batch correction for bioinformatics dataset and domain adaptation for digit datasets

Data

Hyperbolic representation

Run all the batches/domains with the code at the link https://github.com/facebookresearch/poincare-embeddings

Set the hyperparameters with manifold lorentz, learning rate 0.001, train threads 2, and batch size 20.

Demo - HPA

from manifold_func import *

# data is the obtained hyperbolic representation in the Lorentz model
# the data type is a list that each list item represents the data from one batch/domain 
HPA_data = HPA_align_tan(data)
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Comments
  • Some questions about transferring scRNA-seq data into hyperbolic space

    Some questions about transferring scRNA-seq data into hyperbolic space

    Hello, I am the listener in NeuriPS who is interested in the application of HPA in scRNA-seq data. I tried to use the code here to process scRNA-seq data but got this error: image Could you please give me any hints? Thanks.

    opened by HelloWorldLTY 2
  • Some questions related to the code running in HPA

    Some questions related to the code running in HPA

    Hello, sorry to disturb you again, I am Tianyu. I tried to get the embeddings value using facebook team's method but I still found some problem to run your hpa. The error comes from this code: 26ef8ec16c27b6283d66afa14845528 I will receive an error saying that the Lorentz inner product method cannot handle with data whose types are not torch.tensor. I think the problem is caused by tmp, which is a int. Therefore, I wonder is it acceptable for me to take a look at the code you used for evaluating single-cell data? Many thanks to your kindness!

    Sincerely, Tianyu

    opened by HelloWorldLTY 1
  • Pretrained embeddings

    Pretrained embeddings

    Hi!

    Thank you for open sourcing the code of this very interesting work!

    Could you share the embeddings of the dataset of gene expression? Or at least the code to preprocess the data. It would help to replicate the experiments in the same settings.

    Thank you in advance!

    opened by clbonet 2
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Ronen Talmon's Lab
Associate Professor of electrical engineering at the Technion in Haifa, Israel. This page holds code repositories of my publications.
Ronen Talmon's Lab
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