Charlotte Bunne

• PhD Student
• External Website
• bunnec@inf.ethz.ch
• CAB G65
• +41 44 632 31 83
• I am a PhD student in Computer Science at 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, and visited the Broad Institute of MIT and Harvard as a research fellow. Before, I worked with Stefanie Jegelka as a Master student at MIT. During my Master’s studies in Computational Biology, I also interned at IBM Research. My research focuses on neural optimal transport and its connections to control theory, diffusion models, and dynamical systems with applications in single-cell biology and protein design.

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Publications

2024

Optimal Transport for Single-Cell and Spatial Omics C. Bunne, G. Schiebinger, A. Krause, A. Regev, M. Cuturi In Nature Reviews Methods Primers, 2024 [bibtex] [abstract] [pdf] [doi]

2023

Aligned Diffusion Schrödinger Bridges V. R. Somnath, M. Pariset, Y. P. Hsieh, M. R. Martinez, A. Krause, C. Bunne In Conference on Uncertainty in Artificial Intelligence (UAI), 2023 [bibtex] [abstract] [pdf]

Learning Single-Cell Perturbation Responses using Neural Optimal Transport C. Bunne, S. G. Stark, G. Gut, J. S. del Castillo, M. Levesque, K. V. Lehmann, L. Pelkmans, A. Krause, G. Ratsch In Nature Methods, Nature Publishing Group, 2023 [bibtex] [abstract] [pdf]

Unbalanced Diffusion Schrödinger Bridge M. Pariset, Y. P. Hsieh, C. Bunne, A. Krause, V. D. Bortoli In arXiv Preprint arXiv:2306.09099v1, 2023 [bibtex] [abstract] [pdf]

The Schrödinger Bridge between Gaussian Measures has a Closed Form C. Bunne, Y. P. Hsieh, M. Cuturi, A. Krause In Proc. International Conference on Artificial Intelligence and Statistics (AISTATS), 2023 Oral presentation [bibtex] [abstract] [pdf]

Neural Unbalanced Optimal Transport via Cycle-Consistent Semi-Couplings F. Lübeck*, C. Bunne*, G. Gut, J. S. del Castillo, L. Pelkmans, D. Alvarez-Melis In arXiv preprint arXiv:2209.15621, 2023 [bibtex] [abstract] [pdf]

2022

Supervised Training of Conditional Monge Maps C. Bunne, A. Krause, M. Cuturi In Proc. Neural Information Processing Systems (NeurIPS), 2022 [bibtex] [abstract] [pdf]

Independent SE(3)-Equivariant Models for End-to-End Rigid Protein Docking O. E. Ganea*, X. Huang*, C. Bunne, Y. Bian, R. Barzilay, T. S. Jaakkola, A. Krause In Proc. International Conference on Learning Representations (ICLR), 2022 Spotlight presentation [bibtex] [abstract] [pdf]

Proximal Optimal Transport Modeling of Population Dynamics C. Bunne, L. Meng-Papaxanthos, A. Krause, M. Cuturi In Proc. International Conference on Artificial Intelligence and Statistics (AISTATS), 2022 Best Paper Award at ICML Time-Series Workshop [bibtex] [abstract] [pdf]

Machine intelligence for chemical reaction space P. Schwaller, A. C. Vaucher, R. Laplaza, C. Bunne, A. Krause, C. Corminboeuf, T. Laino In WIREs Computational Molecular Science Advanced Reviews, 2022 [bibtex] [abstract] [pdf] [doi]

Optimal Transport Tools (OTT): A JAX Toolbox for all things Wasserstein M. Cuturi, L. Meng-Papaxanthos, Y. Tian, C. Bunne, G. Davis, O. Teboul In arXiv Preprint arXiv:2201.12324, 2022 [bibtex] [abstract] [pdf]

2021

Multi-Scale Representation Learning on Proteins V. R. Somnath*, C. Bunne*, A. Krause In Proc. Neural Information Processing Systems (NeurIPS), 2021 [bibtex] [abstract] [pdf] [code]

Learning Graph Models for Retrosynthesis Prediction V. R. Somnath, C. Bunne, C. W. Coley, A. Krause, R. Barzilay In Proc. Neural Information Processing Systems (NeurIPS), 2021 Best Paper Award at ICML on Graph Representation Learning and Beyond [bibtex] [abstract] [pdf] [code]

2019

Learning Generative Models across Incomparable Spaces C. Bunne, D. Alvarez-Melis, A. Krause, S. Jegelka In Proc. International Conference on Machine Learning (ICML), 2019 Best Paper Award at NeurIPS Workshop on Relational Representation Learning [bibtex] [abstract] [pdf]