mixup: Beyond empirical risk minimization H Zhang, M Cisse, YN Dauphin, D Lopez-Paz ICLR, 2018 | 11609 | 2018 |
Gradient Episodic Memory for Continual Learning D Lopez-Paz, MA Ranzato NeurIPS, 2017 | 2968 | 2017 |
Invariant risk minimization M Arjovsky, L Bottou, I Gulrajani, D Lopez-Paz arXiv, 2019 | 2353 | 2019 |
Manifold mixup: learning better representations by interpolating hidden states V Verma, A Lamb, C Beckham, A Najafi, A Courville, I Mitliagkas, ... ICML, 2019 | 1485* | 2019 |
In Search of Lost Domain Generalization I Gulrajani, D Lopez-Paz ICLR, 2021 | 1241 | 2021 |
Interpolation consistency training for semi-supervised learning V Verma, A Lamb, J Kannala, Y Bengio, D Lopez-Paz IJCAI, 2019 | 875 | 2019 |
Unifying distillation and privileged information D Lopez-Paz, L Bottou, B Schölkopf, V Vapnik ICLR, 2016 | 555 | 2016 |
Optimizing the latent space of generative networks P Bojanowski, A Joulin, D Lopez-Paz, A Szlam ICML, 2018 | 509 | 2018 |
Revisiting classifier two-sample tests D Lopez-Paz, M Oquab ICLR, 2017 | 477 | 2017 |
Single-Model Uncertainties for Deep Learning N Tagasovska, D Lopez-Paz NeurIPS, 2019 | 321 | 2019 |
Discovering causal signals in images D Lopez-Paz, R Nishihara, S Chintala, B Scholkopf, L Bottou CVPR, 2017 | 281 | 2017 |
The Randomized Dependence Coefficient D Lopez-Paz, P Hennig, B Schölkopf NeurIPS, 2013 | 259 | 2013 |
Using hindsight to anchor past knowledge in continual learning A Chaudhry, A Gordo, PK Dokania, P Torr, D Lopez-Paz AAAI, 2021 | 241 | 2021 |
Randomized Nonlinear Component Analysis D Lopez-Paz, S Sra, A Smola, Z Ghahramani, B Schölkopf ICML, 2014 | 233 | 2014 |
Towards a Learning Theory of Cause-Effect Inference D Lopez-Paz, K Muandet, B Schölkopf, I Tolstikhin ICML, 2015 | 216 | 2015 |
Learning functional causal models with generative neural networks O Goudet, D Kalainathan, P Caillou, I Guyon, D Lopez-Paz, M Sebag Explainable and Interpretable Models in Computer Vision and Machine Learning …, 2018 | 182 | 2018 |
Simple data balancing achieves competitive worst-group-accuracy BY Idrissi, M Arjovsky, M Pezeshki, D Lopez-Paz Conference on Causal Learning and Reasoning, 336-351, 2022 | 167 | 2022 |
Predicting cellular responses to complex perturbations in high‐throughput screens M Lotfollahi, A Klimovskaia Susmelj, C De Donno, L Hetzel, Y Ji, IL Ibarra, ... Molecular systems biology 19 (6), e11517, 2023 | 147* | 2023 |
SAM: Structural Agnostic Model, causal discovery and penalized adversarial learning D Kalainathan, O Goudet, I Guyon, D Lopez-Paz, M Sebag arXiv, 2018 | 141* | 2018 |
First-order adversarial vulnerability of neural networks and input dimension CJ Simon-Gabriel, Y Ollivier, L Bottou, B Schölkopf, D Lopez-Paz ICML, 2019 | 126 | 2019 |