David Lopez-Paz

Research Scientist

I’m a research scientist at Facebook AI Research, Paris, France. Prior to joining Facebook in 2016, I received my PhD from the Max Planck Institute for Intelligent Systems and the University of Cambridge, advised by Bernhard Schölkopf and Zoubin Ghahramani. Before that, I obtained a degree in computer science from the Universidad Autonoma de Madrid in 2011. During my studies, I interned at various industries, including the European Space Agency, Google Research and the Red Bull Formula 1 team.

The goal of my research is to develop theory and algorithms for unsupervised causal inference, and their use to build machines which are able to reason and learn about the world using less data.


Learning theory, causal inference, nonconvex optimization, un/semi/supervised learning and new learning paradigms

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Latest Publications

ICLR - April 25, 2020

Permutation Equivariant Models for Compositional Generalization in Language

Jonathan Gordon, David Lopez-Paz, Marco Baroni, Diane Bouchacourt

ICML - June 9, 2019

Manifold Mixup: Better Representations by Interpolating Hidden States

Vikas Verma, Alex Lamb, Christopher Beckham, Amir Najafi, Ioannis Mitliagkas, David Lopez-Paz, Yoshua Bengio

ICML - June 9, 2019

First-order Adversarial Vulnerability of Neural Networks and Input Dimension

Carl-Johann Simon-Gabriel, Yann Ollivier, Bernhard Scholkopf, Léon Bottou, David Lopez-Paz

ICML 2018 - July 10, 2018

Optimizing the Latent Space of Generative Networks

Piotr Bojanowski, Armand Joulin, David Lopez-Paz, Arthur Szlam

ICLR 2018 - April 30, 2018

mixup: Beyond Empirical Risk Minimization

Hongyi Zhang, Moustapha Cisse, Yann Dauphin, David Lopez-Paz

ICLR 2018 - April 30, 2018

Easing Non-Convex Optimization with Neural Networks

David Lopez-Paz, Levent Sagun

arXiv - March 12, 2018

Geometrical Insights for Implicit Generative Modeling

Léon Bottou, Martin Arjovsky, David Lopez-Paz, Maxime Oquab

NIPS 2017 - December 4, 2017

Gradient Episodic Memory for Continual Learning

David Lopez-Paz, Marc'Aurelio Ranzato

CVPR 2017 - July 21, 2017

Discovering Causal Signals in Images

David Lopez-Paz, Robert Nishihara, Soumith Chintala, Bernhard Scholkopf, Léon Bottou

PETS 2017 - July 18, 2017

Patient-Driven Privacy through Generalized Distillation

Z. Berkay Celik, David Lopez-Paz, Patrick McDaniel

ICLR 2017 - April 24, 2017

Revisiting Classifier Two-Sample Tests for GAN Evaluation and Causal Discovery

David Lopez-Paz, Maxime Oquab

ArXiv - August 12, 2015

No Regret Bound for Extreme Bandits

Robert Nishihara, David Lopez-Paz, Léon Bottou

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