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.
Interests
Learning theory, causal inference, nonconvex optimization, un/semi/supervised learning and new learning paradigms
Related Links
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
First-order Adversarial Vulnerability of Neural Networks and Input Dimension
Carl-Johann Simon-Gabriel, Yann Ollivier, Bernhard Scholkopf, Leon Bottou, David Lopez-Paz
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 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
Leon 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, Leon 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, Leon Bottou
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