David Lopez-Paz
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
24
Venues
6
Active years
2013–2025
Best venue rank
A*
Where they publish
Papers
24 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2025 | ICLR | The Pitfalls of Memorization: When Memorization Hurts Generalization. | Reza Bayat, Mohammad Pezeshki, Elvis Dohmatob, David Lopez-Paz, Pascal Vincent |
| 2024 | ICLR | Context is Environment. | Sharut Gupta, Stefanie Jegelka, David Lopez-Paz, Kartik Ahuja |
| 2024 | ICML | Better & Faster Large Language Models via Multi-token Prediction. | Fabian Gloeckle, Badr Youbi Idrissi, Baptiste Rozire, David Lopez-Paz, Gabriel Synnaeve |
| 2024 | ICML | Discovering Environments with XRM. | Mohammad Pezeshki, Diane Bouchacourt, Mark Ibrahim, Nicolas Ballas, Pascal Vincent, David Lopez-Paz |
| 2023 | ICLR | 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 |
| 2023 | ICML | Why does Throwing Away Data Improve Worst-Group Error? | Kamalika Chaudhuri, Kartik Ahuja, Martn Arjovsky, David Lopez-Paz |
| 2023 | ICML | Model Ratatouille: Recycling Diverse Models for Out-of-Distribution Generalization. | Alexandre Ram, Kartik Ahuja, Jianyu Zhang, Matthieu Cord, Lon Bottou, David Lopez-Paz |
| 2022 | ICML | Rich Feature Construction for the Optimization-Generalization Dilemma. | Jianyu Zhang, David Lopez-Paz, Lon Bottou |
| 2021 | AAAI | Using Hindsight to Anchor Past Knowledge in Continual Learning. | Arslan Chaudhry, Albert Gordo, Puneet K. Dokania, Philip H. S. Torr, David Lopez-Paz |
| 2021 | ICLR | In Search of Lost Domain Generalization. | Ishaan Gulrajani, David Lopez-Paz |
| 2020 | ICLR | Permutation Equivariant Models for Compositional Generalization in Language. | Jonathan Gordon, David Lopez-Paz, Marco Baroni, Diane Bouchacourt |
| 2019 | ICML | First-Order Adversarial Vulnerability of Neural Networks and Input Dimension. | Carl-Johann Simon-Gabriel, Yann Ollivier, Lon Bottou, Bernhard Schlkopf, David Lopez-Paz |
| 2019 | ICML | Manifold Mixup: Better Representations by Interpolating Hidden States. | Vikas Verma, Alex Lamb, Christopher Beckham, Amir Najafi, Ioannis Mitliagkas, David Lopez-Paz, Yoshua Bengio |
| 2019 | IJCAI | Interpolation Consistency Training for Semi-supervised Learning. | Vikas Verma, Alex Lamb, Juho Kannala, Yoshua Bengio, David Lopez-Paz |
| 2018 | ICLR | Easing non-convex optimization with neural networks. | David Lopez-Paz, Levent Sagun |
| 2018 | ICLR | Causal Discovery Using Proxy Variables. | Mateo Rojas-Carulla, Marco Baroni, David Lopez-Paz |
| 2018 | ICLR | mixup: Beyond Empirical Risk Minimization. | Hongyi Zhang, Moustapha Ciss, Yann N. Dauphin, David Lopez-Paz |
| 2018 | ICML | Optimizing the Latent Space of Generative Networks. | Piotr Bojanowski, Armand Joulin, David Lopez-Paz, Arthur Szlam |
| 2017 | CVPR | Discovering Causal Signals in Images. | David Lopez-Paz, Robert Nishihara, Soumith Chintala, Bernhard Schlkopf, Lon Bottou |
| 2017 | ICLR | Revisiting Classifier Two-Sample Tests. | David Lopez-Paz, Maxime Oquab |
| 2016 | AISTATS | No Regret Bound for Extreme Bandits. | Robert Nishihara, David Lopez-Paz, Lon Bottou |
| 2015 | ICML | Towards a Learning Theory of Cause-Effect Inference. | David Lopez-Paz, Krikamol Muandet, Bernhard Schlkopf, Ilya O. Tolstikhin |
| 2014 | ICML | Randomized Nonlinear Component Analysis. | David Lopez-Paz, Suvrit Sra, Alexander J. Smola, Zoubin Ghahramani, Bernhard Schlkopf |
| 2013 | ICML | Gaussian Process Vine Copulas for Multivariate Dependence. | David Lopez-Paz, Jos Miguel Hernndez-Lobato, Zoubin Ghahramani |