← Authors

David Lopez-paz

30 papers · 2012–2025 · 9 conferences · across top CS/AI conferences

Achievements

🐣 Hot Topic Early Bird 🌈 Renaissance Researcher (5) 🐝 Cross-Pollinator (14) πŸŒ‰ Interdisciplinary Bridge πŸƒ Academic Marathon (13) πŸ—ΊοΈ Taxonomy Completionist (18) 🧭 Keyword Pioneer 🌍 Conference Polyglot (9) πŸ† Keyword Champion (2) πŸ† Grand Slam ❓ The Questioner πŸ—ƒοΈ Keyword Collector (59) πŸ“ˆ Trend Setter πŸ”₯ Unstoppable (14) πŸš€ Conference Pioneer ⚑ Prolific Year (5) πŸ’Ž Century Club (30)

Conferences

ICML (10) ICLR (6) NIPS (6) JMLR (3) AAAI (1) AISTATS (1) CLEAR (1) CVPR (1) IJCAI (1)

Top co-authors

Bernhard SchΓΆlkopf (5) LΓ©on Bottou (5) Badr Youbi Idrissi (3) Mohammad Pezeshki (3) Kartik Ahuja (3) Diane Bouchacourt (3) Pascal Vincent (3) Krikamol Muandet (2) Yoshua Bengio (2) Nicolas Ballas (2)

Research topics

Statistics (1)

Keywords

causal discovery (3) neural network (3) representation learning (3) causal inference (3) transfer learning (2) semi-supervised learning (2) episodic memory (2) domain generalization (2) vine copula (2) catastrophic forgetting (2) kernel mean embedding (2) out-of-distribution generalization (2) marginal distribution (2) continual learning (2) bayesian inference (1) principal component analysis (1) domain adaptation (1) adversarial learning (1) epistemic uncertainty (1) spectral clustering (1)

Papers

The Pitfalls of Memorization: When Memorization Hurts Generalization ICLR 2025
Better & Faster Large Language Models via Multi-token Prediction ICML 2024
Context is Environment ICLR 2024
Discovering Environments with XRM ICML 2024
Model Ratatouille: Recycling Diverse Models for Out-of-Distribution Generalization ICML 2023
ImageNet-X: Understanding Model Mistakes with Factor of Variation Annotations ICLR 2023
Why does Throwing Away Data Improve Worst-Group Error? ICML 2023
Structural Agnostic Modeling: Adversarial Learning of Causal Graphs JMLR 2022
Simple data balancing achieves competitive worst-group-accuracy CLEAR 2022
Rich Feature Construction for the Optimization-Generalization Dilemma ICML 2022
An Empirical Investigation of Domain Generalization with Empirical Risk Minimizers NIPS 2021
In Search of Lost Domain Generalization ICLR 2021
Using Hindsight to Anchor Past Knowledge in Continual Learning AAAI 2021
Permutation Equivariant Models for Compositional Generalization in Language ICLR 2020
First-Order Adversarial Vulnerability of Neural Networks and Input Dimension ICML 2019
Manifold Mixup: Better Representations by Interpolating Hidden States ICML 2019
Interpolation Consistency Training for Semi-supervised Learning IJCAI 2019
Learning about an exponential amount of conditional distributions NIPS 2019
Single-Model Uncertainties for Deep Learning NIPS 2019
mixup: Beyond Empirical Risk Minimization ICLR 2018
Gradient Episodic Memory for Continual Learning NIPS 2017
Discovering Causal Signals in Images CVPR 2017
Non-linear Causal Inference using Gaussianity Measures JMLR 2016
No Regret Bound for Extreme Bandits AISTATS 2016
Towards a Learning Theory of Cause-Effect Inference ICML 2015
The Randomized Causation Coefficient JMLR 2015
Randomized Nonlinear Component Analysis ICML 2014
Gaussian Process Vine Copulas for Multivariate Dependence ICML 2013
The Randomized Dependence Coefficient NIPS 2013
Semi-Supervised Domain Adaptation with Non-Parametric Copulas NIPS 2012