Hugues Van Assel

Postdoctoral Fellow at Genentech, South San Francisco CA

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I am a postdoc at Genentech with Aviv Regev, working on machine learning for science and drug discovery. My research interests include representation learning, multi-modal learning, dimensionality reduction and optimal transport.

Open-Source. I enjoy building and sharing open-source tools:

TorchDR
PyTorch toolbox for dimensionality reduction with state-of-the-art speed on single and multi-GPU.
stable-pretraining
PyTorch library for foundation model pretraining with real-time training monitoring.

Background. I did my PhD in the math department of ENS Lyon, supervised by Titouan Vayer and Aurélien Garivier. During my PhD, I visited the GalilAI group at Brown University to work on self-supervised learning. Prior to my PhD, I was a student at Ecole polytechnique and MVA.


selected publications

  1. NeurIPS
    Joint Embedding vs Reconstruction: Provable Benefits of Latent Space Prediction for Self-Supervised Learning
    Hugues Van Assel, Mark Ibrahim, Tommaso Biancalani, Aviv Regev, and Randall Balestriero
    Advances in Neural Information Processing Systems (Spotlight), 2025
    arXiv Blog Poster
  2. TMLR
    Distributional Reduction: Unifying Dimensionality Reduction and Clustering with Gromov-Wasserstein
    Hugues Van Assel, Cédric Vincent-Cuaz, Nicolas Courty, Rémi Flamary, Pascal Frossard, and Titouan Vayer
    Transactions on Machine Learning Research, 2024
    arXiv
  3. NeurIPS
    SNEkhorn: Dimension Reduction with Symmetric Entropic Affinities
    Hugues Van Assel, Titouan Vayer, Rémi Flamary, and Nicolas Courty
    Advances in Neural Information Processing Systems, 2023
    arXiv Poster
  4. NeurIPS
    A Probabilistic Graph Coupling View of Dimension Reduction
    Hugues Van Assel, Thibault Espinasse, Julien Chiquet, and Franck Picard
    Advances in Neural Information Processing Systems, 2022
    arXiv Poster