GitHub

👋 I recently joined GenBio.ai as a research scientist. Before that, I completed my PhD in machine learning and computational biology under the joint supervision of Laura Cantini at Institut Pasteur and Gabriel Peyré at ENS PSL. My research focused on leveraging optimal transport techniques for analyzing single-cell multiomics data, bridging the fields of machine learning and genomics.

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  1. Learning cell fate landscapes from spatial transcriptomics using Fused Gromov-Wasserstein

    Python 32 5

  2. Single-cell multi-omics integration using Optimal Transport

    Python 55 5

  3. Python package for the ICML 2022 paper "Unsupervised Ground Metric Learning Using Wasserstein Singular Vectors".

    Python 10 1

  4. This Python package will allow you to replicate the experiments from our research on applying Optimal Transport as a similarity metric in between single-cell omics data.

    Python 43 8

Read the original on github.com ↗