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David Lopez-Paz
David Lopez-Paz
AI at Meta
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mixup: Beyond empirical risk minimization
H Zhang, M Cisse, YN Dauphin, D Lopez-Paz
ICLR, 2018
110922018
Gradient Episodic Memory for Continual Learning
D Lopez-Paz, MA Ranzato
NeurIPS, 2017
28292017
Invariant risk minimization
M Arjovsky, L Bottou, I Gulrajani, D Lopez-Paz
arXiv, 2019
22132019
Manifold mixup: learning better representations by interpolating hidden states
V Verma, A Lamb, C Beckham, A Najafi, A Courville, I Mitliagkas, ...
ICML, 2019
1418*2019
In Search of Lost Domain Generalization
I Gulrajani, D Lopez-Paz
ICLR, 2021
11572021
Interpolation consistency training for semi-supervised learning
V Verma, A Lamb, J Kannala, Y Bengio, D Lopez-Paz
IJCAI, 2019
8452019
Unifying distillation and privileged information
D Lopez-Paz, L Bottou, B Schölkopf, V Vapnik
ICLR, 2016
5422016
Optimizing the latent space of generative networks
P Bojanowski, A Joulin, D Lopez-Paz, A Szlam
ICML, 2018
5002018
Revisiting classifier two-sample tests
D Lopez-Paz, M Oquab
ICLR, 2017
4542017
Single-Model Uncertainties for Deep Learning
N Tagasovska, D Lopez-Paz
NeurIPS, 2019
3112019
Discovering causal signals in images
D Lopez-Paz, R Nishihara, S Chintala, B Scholkopf, L Bottou
CVPR, 2017
2702017
The Randomized Dependence Coefficient
D Lopez-Paz, P Hennig, B Schölkopf
NeurIPS, 2013
2542013
Using hindsight to anchor past knowledge in continual learning
A Chaudhry, A Gordo, PK Dokania, P Torr, D Lopez-Paz
AAAI, 2021
2322021
Randomized Nonlinear Component Analysis
D Lopez-Paz, S Sra, A Smola, Z Ghahramani, B Schölkopf
ICML, 2014
2322014
Towards a Learning Theory of Cause-Effect Inference
D Lopez-Paz, K Muandet, B Schölkopf, I Tolstikhin
ICML, 2015
2112015
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
1712018
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
1482022
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
131*2023
SAM: Structural Agnostic Model, causal discovery and penalized adversarial learning
D Kalainathan, O Goudet, I Guyon, D Lopez-Paz, M Sebag
arXiv, 2018
131*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
1172019
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