Quentin Berthet

Quentin Berthet

I am a Research Scientist in the Brain team of Google Research, in Paris. I work on core Machine Learning, with interests in Statistics and Optimization to tackle these problems. Before coming to Google, I was a lecturer (tenured faculty position) at the University of Cambridge (Statistical Laboratory). Before that I was a CMI postdoc at Caltech. I did my Ph.D. at Princeton University and I am an alumni of Ecole Polytechnique. [Homepage]
Authored Publications
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    Google
DeepConsensus improves the accuracy of sequences with a gap-aware sequence transformer
Aaron Wenger
Andrew Walker Carroll
Armin Töpfer
Ashish Teku Vaswani
Daniel Cook
Felipe Llinares
Gunjan Baid
Howard Cheng-Hao Yang
Jean-Philippe Vert
Kishwar Shafin
Maria Nattestad
Waleed Ammar
William J. Rowell
Nature Biotechnology (2022)
How DeepConsensus Works
Aaron Wenger
Anastasiya Belyaeva
Andrew Carroll
Armin Töpfer
Ashish Teku Vaswani
Daniel Cook
Felipe Llinares
Gunjan Baid
Howard Yang
Jean-Philippe Vert
Kishwar Shafin
Maria Nattestad
Waleed Ammar
William J. Rowell
(2022)
Noisy Adaptive Group Testing using Bayesian Sequential Experimental Design
Marco Cuturi
Olivier Teboul
Arnaud Doucet
Jean-Philippe Vert
arXiv (2020)
Stochastic Optimization for Regularized Wasserstein Estimators
Francis Bach
Marin Ballu
submitted to ICML (2020) (to appear)
Fast Differentiable Sorting and Ranking
Olivier Teboul
Josip Djolonga
ICML (2020) (to appear)
Learning with Differentiable Perturbed Optimizers
Olivier Teboul
Marco Cuturi
Jean-Philippe Vert
Francis Bach
Advances in Neural Information Processing Systems 33 (NeurIPS), Curran Associates, Inc. (2020), pp. 9508-9519