Charlotte Bunne

PhD Student in Machine Learning at ETH Zurich and Broad Institute of MIT and Harvard.

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I am a PhD student in Computer Science at the Eidgenössische Technische Hochschule (ETH) Zurich under the supervision of Andreas Krause and Marco Cuturi. I am part of the Institute for Machine Learning and the ETH AI Center. During my PhD, I interned at Google Research and Apple Research, and visited the Broad Institute of MIT and Harvard as a research fellow. Before, I worked with Stefanie Jegelka as a Master student at the Massachusetts Institute of Technology (MIT). During my Master’s studies in Computational Biology, I also interned at IBM Research. My research focuses on dynamic optimal transport and optimal transport across incomparable domains with applications in single-cell genomics and protein design.

Throughout my undergraduate and graduate studies I’ve been a Fellow of the German National Academic Foundation. For my Master’s studies I received the Excellence Scholarship of the ETH Foundation. I am a recipient of the Google Generation Scholarship and holder of the ETH Medal.

Contact: bunnec [at] ethz [dot] ch
Follow: Google Scholar bunnech @_bunnech @bunnech@sigmoid.social

Announcements

Apr, 2023 I am co-organizer of the Molecular Machine Learning Conference (MoML). After the sucess of the first edition at MIT, the second one will take place May 29, 2023 in-person at Mila.
Mar, 2023 I am a Panelist at the Structured Probabilistic Inference & Generative Modeling Workshop taking place at ICML 2023.
Mar, 2023 I am co-organizing the workshop on New Frontiers in Learning, Control, and Dynamical Systems Workshop at ICML 2023.
Nov, 2022 I am invited to speak at the Models, Inference & Algorithms (MIA) Initiative at the Broad Institute of MIT and Harvard.
Aug, 2022 I joined the Broad Institute of MIT and Harvard to work with Anne Carpenter and Shantanu Singh.

Selected Publications

  1. AISTATS
    Oral
    The Schrödinger Bridge between Gaussian Measures has a Closed Form
    Charlotte Bunne*, Ya-Ping Hsieh*, Marco Cuturi, and Andreas Krause
    International Conference on Artificial Intelligence and Statistics (AISTATS), 2023
    ICML Workshop on Continuous Time Methods for Machine Learning, 2022.
    Oral Presentation at AISTATS (Top 1.9% of Submitted Papers).
  2. NeurIPS
    Supervised Training of Conditional Monge Maps
    Charlotte Bunne, Andreas Krause, and Marco Cuturi
    Advances in Neural Information Processing Systems (NeurIPS), 2022
    ICML Workshop on Interpretable Machine Learning in Healthcare (IMLH), 2022.
  3. Nature Methods
    Submission
    Learning Single-Cell Perturbation Responses using Neural Optimal Transport
    Charlotte Bunne*, Stefan Stark*, Gabriele Gut*, Jacobo Sarabia Castillo, Mitchell Levesque, Kjong Van Lehmann, Lucas Pelkmans, Andreas Krause, and Gunnar Rätsch
    Under Review at Nature Methods, 2022
    NeurIPS Workshop on Optimal Transport and Machine Learning (OTML), 2021.
  4. AISTATS
    Best Paper Award
    Proximal Optimal Transport Modeling of Population Dynamics
    Charlotte Bunne, Laetitia Meng-Papaxanthos, Andreas Krause, and Marco Cuturi
    International Conference on Artificial Intelligence and Statistics (AISTATS), 2022
    Best Paper Award and Contributed Talk at ICML Time Series Workshop, 2021.
  5. ICLR
    Independent SE (3)-Equivariant Models for End-to-End Rigid Protein Docking
    Octavian-Eugen Ganea*, Xinyuan Huang*, Charlotte Bunne, Yatao Bian, Regina Barzilay, Tommi Jaakkola, and Andreas Krause
    International Conference on Learning Representations (ICLR), 2022
    Contributed Talk at ELLIS Machine Learning for Molecule Discovery Workshop, 2021.
    Spotlight Talk at ICLR and Ranked Top 15 among 3326 Submissions (Top 0.4%).
  6. Featured Cover
    Machine intelligence for chemical reaction space
    Philippe Schwaller, Alain C Vaucher, Ruben Laplaza, Charlotte Bunne, Andreas Krause, Clemence Corminboeuf, and Teodoro Laino
    Wiley Interdisciplinary Reviews: Computational Molecular Science, 2022
    Selected as Featured Cover of Volume 12, Issue 5.
  7. NeurIPS
    Multi-Scale Representation Learning on Proteins
    Charlotte Bunne*, Vignesh Ram Somnath*, and Andreas Krause
    Advances in Neural Information Processing Systems (NeurIPS), 2021
    Spotlight Talk at ICML Computational Biology Workshop, 2021.
  8. NeurIPS
    Best Paper Award
    Learning Graph Models for Retrosynthesis Prediction
    Vignesh Ram Somnath, Charlotte Bunne, Connor Coley, Andreas Krause, and Regina Barzilay
    Advances in Neural Information Processing Systems (NeurIPS), 2021
    Best Paper Award and Contributed Talk at ICML Workshop on Graph Representation Learning and Beyond, 2019.
  9. ICML
    Best Paper Award
    Learning Generative Models across Incomparable Spaces
    Charlotte Bunne, David Alvarez-Melis, Andreas Krause, and Stefanie Jegelka
    International Conference on Machine Learning (ICML), 2019
    Best Paper Award and Contributed Talk at NeurIPS Workshop on Relational Representation Learning, 2018.