David Lopez-Paz
I am a research scientist at
Facebook AI Research
in Paris, France. Here is my
email
and
public key
.
Publications
Learning about an exponential amount of conditional distributions
Mohamed Ishmael Belghazi
,
Maxime Oquab
Yann LeCun
, David Lopez-Paz
arXiv
, 2018
Interpolation consistency training for semi-supervised learning
Vikas Verma
,
Alex Lamb
,
Juho Kannala
,
Yoshua Bengio
David Lopez-Paz
arXiv
, 2018
Manifold mixup: Better representations by interpolating hidden states
Vikas Verma
,
Alex Lamb
,
Christopher Beckham
,
Amir Najafi
,
Ioannis Mitliagkas
,
Aaron Courville
, David Lopez-Paz,
Yoshua Bengio
arXiv
, 2018
Frequentist uncertainty estimates for deep learning
Natasa Tagasovska
, David Lopez-Paz
NeurIPS Bayesian Deep Learning
, 2018
SAM: Structural Agnostic Model, causal discovery and penalized adversarial learning
Diviyan Kalainathan
,
Olivier Goudet
,
Isabelle Guyon
, David Lopez-Paz,
Michèle Sebag
arXiv
, 2018 (
code
)
Optimizing the latent space of generative networks
Piotr Bojanowski
,
Armand Joulin
, David Lopez-Paz,
Arthur Szlam
ICML
, 2018
Adversarial vulnerability of neural networks increases with input dimension
Carl-Johann Simon-Gabriel
,
Yann Ollivier
,
Bernhard Schölkopf
,
Léon Bottou
, David Lopez-Paz
arXiv
, 2018
Geometrical insights for implicit generative modeling
Léon Bottou
,
Martín Arjovsky
, David Lopez-Paz,
Maxime Oquab
Springer's Braverman Readings in Machine Learning
, 2018
mixup
: Beyond empirical risk minimization
Hongyi Zhang
,
Moustapha Cisse
,
Yann N. Dauphin
, David Lopez-Paz
ICLR
, 2018 (
code
)
Easing non-convex optimization with neural networks
David Lopez-Paz,
Levent Sagun
ICLR Workshops
, 2018 (
code
)
Causal discovery using proxy variables
Mateo Rojas-Carulla
,
Marco Baroni
, David Lopez-Paz
ICLR Workshops
, 2018
Learning Functional Causal Models with Generative Neural Networks
Olivier Goudet
,
Diviyan Kalainathan
,
Philippe Caillou
,
Isabelle Guyon
, David Lopez-Paz,
Michèle Sebag
Springer's Explainable and Interpretable Models in CV and ML
, 2018 (
code
)
Gradient episodic memory for continuum learning
David Lopez-Paz,
Marc'Aurelio Ranzato
NeurIPS
, 2017 (
code
)
Patient-driven privacy control through generalized distillation
Berkay Celik
, David Lopez-Paz,
Patrick McDaniel
IEEE PAC
, 2017
Revisiting classifier two-sample tests
David Lopez-Paz,
Maxime Oquab
ICLR
, 2017 (
code
)
Discovering causal signals in images
David Lopez-Paz,
Robert Nishihara
,
Soumith Chintala
,
Bernhard Schölkopf
,
Léon Bottou
CVPR
, 2017
From dependence to causation
David Lopez-Paz
Doctoral dissertation
, 2016
Causal and statistical learning
Bernhard Schölkopf
,
Dominik Janzing
, David Lopez-Paz
Oberwolfach Reports
, 2016
Unifying distillation and privileged information
David Lopez-Paz,
Léon Bottou
,
Bernhard Schölkopf
,
Vladimir Vapnik
ICLR
, 2016 (
code
)
Minimax lower bounds for realizable transductive classification
Ilya Tolstikhin
, David Lopez-Paz
arXiv
, 2016
No regret bound for extreme bandits
Robert Nishihara
, David Lopez-Paz,
Léon Bottou
AISTATS
, 2016
Non-linear causal inference using Gaussianity measures
Daniel Hernandez-Lobato
,
Pablo Morales Mombiela
, David Lopez-Paz,
Alberto Suarez
JMLR
, 2016 (
code
)
The randomized causation coefficient
David Lopez-Paz,
Krikamol Muandet
,
Benjamin Recht
JMLR
, 2015 (
code
,
talk
)
Towards a learning theory of cause-effect inference
David Lopez-Paz,
Krikamol Muandet
,
Bernhard Schölkopf
,
Ilya Tolstikhin
ICML
, 2015 (
code
)
Randomized nonlinear component analysis
David Lopez-Paz,
Suvrit Sra
,
Alex Smola
,
Zoubin Ghahramani
,
Bernhard Schölkopf
ICML
, 2014 (
code
,
talk
)
Two numerical models of Saturn rings temperature as measured by Cassini
Nicolas Altobelli
, David Lopez-Paz et al.
Icarus
, 2014
The randomized dependence coefficient
David Lopez-Paz,
Philipp Hennig
,
Bernhard Schölkopf
NeurIPS
, 2013 (
code
,
talk
)
Gaussian process vine copulas for multivariate dependence
David Lopez-Paz,
José Miguel Hernández-Lobato
,
Zoubin Ghahramani
ICML
, 2013 (
code
,
talk
)
Semisupervised domain adaptation with nonparametric copulas
David Lopez-Paz,
José Miguel Hernández-Lobato
,
Bernhard Schölkopf
NeurIPS
, 2012 (
code
,
talk
)
Teaching
Statistical causal learning
Bernhard Schölkopf
,
Ilya Tolstikhin
, David Lopez-Paz
Lake Como School of Advanced Studies
, 2017
Causality
David Lopez-Paz
Machine Learning Summer School
, 2017
Randomized algorithms
David Lopez-Paz
Machine Learning Summer School
, 2016
Kernel methods
Rohit Babbar
, David Lopez-Paz,
Krikamol Muandet
Machine Learning Summer School
, 2015
Graphical models in computer vision
Peter Gehler
,
Andreas Geiger
, David Lopez-Paz
University of Tübingen
, 2014/15
Graphical models in computer vision
Peter Gehler
, David Lopez-Paz
University of Tübingen
, 2013/14
Random projections
David Lopez-Paz,
David Duvenaud
,
University of Cambridge
, 2014
Meetings
Causal learning
Martin Arjovsky
,
Christina Heinze-Deml
,
Anna Klimovskaia
,
Maxime Oquab
,
Léon Bottou
, David Lopez-Paz
NeurIPS
, 2018
The theory of generative adversarial networks
Sebastian Nowozin
, David Lopez-Paz
DALI
, 2017 (
videos
)
Workshop on adversarial training
David Lopez-Paz,
Alec Radford
,
Léon Bottou
NeurIPS
, 2016
Second machine learning in Cambridge meeting
David Lopez-Paz,
Sebastian Nowozin
,
Zoubin Ghahramani
Microsoft Research Cambridge
, 2015
First machine learning in Cambridge meeting
David Lopez-Paz,
Sebastian Nowozin
,
Zoubin Ghahramani
Microsoft Research Cambridge
, 2014
Workshop on randomized methods for machine learning
David Lopez-Paz,
Quoc Le
,
Alex Smola
NeurIPS
, 2013