David Lopez-paz

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

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Achievements

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🗺️ Taxonomy Completionist (52) 🌍 Conference Polyglot · Silver 🏃 Academic Marathon · Half 🌉 Interdisciplinary Bridge · Bronze 🐣 Hot Topic Early Bird

🏆 Grand Slam 📈 Trend Setter 🗃️ Keyword Collector (142) 🚀 Conference Pioneer 🔥 Unstoppable · Silver ❓ The Questioner ⚡ Prolific Year · Productive 💎 Century Club · Bronze 🌈 Renaissance Researcher (5)

Venues

ICML (10) ICLR (6) NeurIPS (6) JMLR (3) AAAI (1) AISTATS (1) CLeaR (1) CVPR (1) IJCAI (1)

Top co-authors

Bernhard Schölkopf (5) Léon 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

Machine Learning (27) Artificial Intelligence (14) Deep Learning (14) Application Areas (12) Learning Types · Machine Learning (11) Optimization & Theory (11) Core AI (9) Core Methods (8) Learning Types · Deep Learning (8) Knowledge & Reasoning (4) Reasoning (4) Architectures (3) Bayesian & Probabilistic · Machine Learning (3) Bayesian & Probabilistic · Artificial Intelligence (3) Learning Paradigms (3)

Keywords

domain generalization (4) neural network (4) empirical risk minimization (4) out-of-distribution generalization (3) causal discovery (3) causal inference (3) representation learning (3) distribution shift (3) image classification (2) marginal distribution (2) vine copula (2) continual learning (2) transfer learning (2) domain adaptation (2) catastrophic forgetting (2) episodic memory (2) feature learning (2) semi-supervised learning (2) data augmentation (2) kernel mean embedding (2)

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 ImageNet-X: Understanding Model Mistakes with Factor of Variation Annotations ICLR 2023 Model Ratatouille: Recycling Diverse Models for Out-of-Distribution Generalization ICML 2023 Why does Throwing Away Data Improve Worst-Group Error? ICML 2023 Rich Feature Construction for the Optimization-Generalization Dilemma ICML 2022 Simple data balancing achieves competitive worst-group-accuracy CLeaR 2022 Structural Agnostic Modeling: Adversarial Learning of Causal Graphs JMLR 2022 An Empirical Investigation of Domain Generalization with Empirical Risk Minimizers NeurIPS 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 Interpolation Consistency Training for Semi-supervised Learning IJCAI 2019 Learning about an exponential amount of conditional distributions NeurIPS 2019 Manifold Mixup: Better Representations by Interpolating Hidden States ICML 2019 Single-Model Uncertainties for Deep Learning NeurIPS 2019 mixup: Beyond Empirical Risk Minimization ICLR 2018 Discovering Causal Signals in Images CVPR 2017 Gradient Episodic Memory for Continual Learning NeurIPS 2017 Non-linear Causal Inference using Gaussianity Measures JMLR 2016 No Regret Bound for Extreme Bandits AISTATS 2016 The Randomized Causation Coefficient JMLR 2015 Towards a Learning Theory of Cause-Effect Inference ICML 2015 Randomized Nonlinear Component Analysis ICML 2014 Gaussian Process Vine Copulas for Multivariate Dependence ICML 2013 The Randomized Dependence Coefficient NeurIPS 2013 Semi-Supervised Domain Adaptation with Non-Parametric Copulas NeurIPS 2012