Ambroise Odonnat

Ph.D. student at Huawei Noah's Ark Lab and Inria.
Jointly supervised by Ievgen Redko, Romain Tavenard and Laetitia Chapel.

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In front of TUM in Munich

I am Ambroise Odonnat, a first-year Ph.D. student at Huawei Noah’s Ark Lab and Inria working on transformers and distribution shifts.

I leverage various mathematical tools to better understand and empirically improve Transformers in settings where training and test data distributions differ. I am also interested in the optimization of neural networks.

Previously, I obtained my master’s degree at ENS Paris-Saclay in 2023 from the Mathematics, Vision, and Machine Learning (MVA) program. I also hold an engineering degree from Ecole des Ponts ParisTech in mathematics and computer science.

I maintain a research blog called logB with my friend Oussama Zekri. Feel free to check it out 🙃. Don’t hesitate to reach out for possible collaborations or questions regarding my research!

news

Oct 02, 2024 📑 New preprint: Large Language Models as Markov Chains.
Sep 25, 2024 🥳 2 papers @ NeurIPS 2024: a spotlight here and MaNo as a poster.
Sep 18, 2024 🤗 Officially starting my Ph.D. at Huawei Noah’s Ark Lab and Inria.
Jul 23, 2024 🎤 Presenting SAMformer @ ICML 2024 in Vienna, Austria.
Jul 18, 2024 🥳 Launch of logB, our research blog with my friend Oussama Zekri.

selected publications

  1. llm_preview.png
    Large Language Models as Markov Chains
    Oussama Zekri* , Ambroise Odonnat*, and 4 more authors
    Preprint, 2024.
  2. logo_ts.png
    Analysing Multi-Task Regression via Random Matrix Theory with Application to Time Series Forecasting
    Romain Ilbert , Malik Tiomoko , and 5 more authors
    NeurIPS Spotlight, 2024.
  3. logo_hands.png
    MANO: Exploiting Matrix Norm for Unsupervised Accuracy Estimation Under Distribution Shifts
    Renchunzi Xie* , Ambroise Odonnat*, and 4 more authors
    NeurIPS, 2024.
  4. transformers.png
    SAMformer: Unlocking the Potential of Transformers in Time Series Forecasting with Sharpness-Aware Minimization and Channel-Wise Attention
    Romain Ilbert* , Ambroise Odonnat*, and 5 more authors
    ICML Oral, 2024.
  5. diversity.png
    Leveraging Ensemble Diversity for Robust Self-Training in the Presence of Sample Selection Bias
    Ambroise Odonnat, Vasilii Feofanov , and 1 more author
    AISTATS, 2024.