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Lopez-Paz, David
40 publications
NeurIPS
2025
From Bytes to Ideas: Language Modeling with Autoregressive U-Nets
Mathurin Videau
,
Badr Youbi Idrissi
,
Alessandro Leite
,
Marc Schoenauer
,
Olivier Teytaud
,
David Lopez-Paz
ICLR
2025
The Pitfalls of Memorization: When Memorization Hurts Generalization
Reza Bayat
,
Mohammad Pezeshki
,
Elvis Dohmatob
,
David Lopez-Paz
,
Pascal Vincent
ICLRW
2025
Unveiling Simplicities of Attention: Adaptive Long-Context Head Identification
Konstantin Donhauser
,
Charles Arnal
,
Mohammad Pezeshki
,
Vivien Cabannes
,
David Lopez-Paz
,
Kartik Ahuja
ICML
2024
Better & Faster Large Language Models via Multi-Token Prediction
Fabian Gloeckle
,
Badr Youbi Idrissi
,
Baptiste Roziere
,
David Lopez-Paz
,
Gabriel Synnaeve
ICLR
2024
Context Is Environment
Sharut Gupta
,
Stefanie Jegelka
,
David Lopez-Paz
,
Kartik Ahuja
ICML
2024
Discovering Environments with XRM
Mohammad Pezeshki
,
Diane Bouchacourt
,
Mark Ibrahim
,
Nicolas Ballas
,
Pascal Vincent
,
David Lopez-Paz
NeurIPSW
2024
The Pitfalls of Memorization: When Memorization Hinders Generalization
Reza Bayat
,
Mohammad Pezeshki
,
Elvis Dohmatob
,
David Lopez-Paz
,
Pascal Vincent
ICMLW
2023
A Closer Look at In-Context Learning Under Distribution Shifts
Kartik Ahuja
,
David Lopez-Paz
NeurIPSW
2023
Context Is Environment
Sharut Gupta
,
David Lopez-Paz
,
Stefanie Jegelka
,
Kartik Ahuja
NeurIPSW
2023
Context Is Environment
Sharut Gupta
,
David Lopez-Paz
,
Stefanie Jegelka
,
Kartik Ahuja
NeurIPSW
2023
Discovering Environments with XRM
Mohammad Pezeshki
,
Diane Bouchacourt
,
Mark Ibrahim
,
Nicolas Ballas
,
Pascal Vincent
,
David Lopez-Paz
ICLR
2023
ImageNet-X: Understanding Model Mistakes with Factor of Variation Annotations
Badr Youbi Idrissi
,
Diane Bouchacourt
,
Randall Balestriero
,
Ivan Evtimov
,
Caner Hazirbas
,
Nicolas Ballas
,
Pascal Vincent
,
Michal Drozdzal
,
David Lopez-Paz
,
Mark Ibrahim
ICML
2023
Model Ratatouille: Recycling Diverse Models for Out-of-Distribution Generalization
Alexandre Rame
,
Kartik Ahuja
,
Jianyu Zhang
,
Matthieu Cord
,
Leon Bottou
,
David Lopez-Paz
ICML
2023
Why Does Throwing Away Data Improve Worst-Group Error?
Kamalika Chaudhuri
,
Kartik Ahuja
,
Martin Arjovsky
,
David Lopez-Paz
NeurIPSW
2022
Pre-Train, Fine-Tune, Interpolate: A Three-Stage Strategy for Domain Generalization
Alexandre Rame
,
Jianyu Zhang
,
Leon Bottou
,
David Lopez-Paz
ICML
2022
Rich Feature Construction for the Optimization-Generalization Dilemma
Jianyu Zhang
,
David Lopez-Paz
,
Leon Bottou
CLeaR
2022
Simple Data Balancing Achieves Competitive Worst-Group-Accuracy
Badr Youbi Idrissi
,
Martin Arjovsky
,
Mohammad Pezeshki
,
David Lopez-Paz
JMLR
2022
Structural Agnostic Modeling: Adversarial Learning of Causal Graphs
Diviyan Kalainathan
,
Olivier Goudet
,
Isabelle Guyon
,
David Lopez-Paz
,
Michèle Sebag
NeurIPS
2021
An Empirical Investigation of Domain Generalization with Empirical Risk Minimizers
Ramakrishna Vedantam
,
David Lopez-Paz
,
David J Schwab
ICLR
2021
In Search of Lost Domain Generalization
Ishaan Gulrajani
,
David Lopez-Paz
AAAI
2021
Using Hindsight to Anchor past Knowledge in Continual Learning
Arslan Chaudhry
,
Albert Gordo
,
Puneet K. Dokania
,
Philip H. S. Torr
,
David Lopez-Paz
ICLR
2020
Permutation Equivariant Models for Compositional Generalization in Language
Jonathan Gordon
,
David Lopez-Paz
,
Marco Baroni
,
Diane Bouchacourt
ICML
2019
First-Order Adversarial Vulnerability of Neural Networks and Input Dimension
Carl-Johann Simon-Gabriel
,
Yann Ollivier
,
Leon Bottou
,
Bernhard Schölkopf
,
David Lopez-Paz
IJCAI
2019
Interpolation Consistency Training for Semi-Supervised Learning
Vikas Verma
,
Alex Lamb
,
Juho Kannala
,
Yoshua Bengio
,
David Lopez-Paz
NeurIPS
2019
Learning About an Exponential Amount of Conditional Distributions
Mohamed Belghazi
,
Maxime Oquab
,
David Lopez-Paz
ICML
2019
Manifold Mixup: Better Representations by Interpolating Hidden States
Vikas Verma
,
Alex Lamb
,
Christopher Beckham
,
Amir Najafi
,
Ioannis Mitliagkas
,
David Lopez-Paz
,
Yoshua Bengio
NeurIPS
2019
Single-Model Uncertainties for Deep Learning
Natasa Tagasovska
,
David Lopez-Paz
ICLR
2018
Mixup: Beyond Empirical Risk Minimization
Hongyi Zhang
,
Moustapha Cisse
,
Yann N. Dauphin
,
David Lopez-Paz
CVPR
2017
Discovering Causal Signals in Images
David Lopez-Paz
,
Robert Nishihara
,
Soumith Chintala
,
Bernhard Scholkopf
,
Leon Bottou
NeurIPS
2017
Gradient Episodic Memory for Continual Learning
David Lopez-Paz
,
Marc'Aurelio Ranzato
ICLR
2017
Revisiting Classifier Two-Sample Tests
David Lopez-Paz
,
Maxime Oquab
AISTATS
2016
No Regret Bound for Extreme Bandits
Robert Nishihara
,
David Lopez-Paz
,
Léon Bottou
JMLR
2016
Non-Linear Causal Inference Using Gaussianity Measures
Daniel Hernández-Lobato
,
Pablo Morales-Mombiela
,
David Lopez-Paz
,
Alberto Suárez
ICLR
2016
Unifying Distillation and Privileged Information
David Lopez-Paz
,
Léon Bottou
,
Bernhard Schölkopf
,
Vladimir Vapnik
JMLR
2015
The Randomized Causation Coefficient
David Lopez-Paz
,
Krikamol Muandet
,
Benjamin Recht
ICML
2015
Towards a Learning Theory of Cause-Effect Inference
David Lopez-Paz
,
Krikamol Muandet
,
Bernhard Schölkopf
,
Iliya Tolstikhin
ICML
2014
Randomized Nonlinear Component Analysis
David Lopez-Paz
,
Suvrit Sra
,
Alex Smola
,
Zoubin Ghahramani
,
Bernhard Schoelkopf
ICML
2013
Gaussian Process Vine Copulas for Multivariate Dependence
David Lopez-Paz
,
Jose Miguel Hernández-Lobato
,
Ghahramani Zoubin
NeurIPS
2013
The Randomized Dependence Coefficient
David Lopez-Paz
,
Philipp Hennig
,
Bernhard Schölkopf
NeurIPS
2012
Semi-Supervised Domain Adaptation with Non-Parametric Copulas
David Lopez-paz
,
Jose M. Hernández-lobato
,
Bernhard Schölkopf