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Elliot Creager

13 papers · 2018–2026 · 5 venues · across top CS/AI venues

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Achievements

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+6 more ↓ πŸ—ΊοΈ Taxonomy Completionist (29) πŸƒ Academic Marathon Β· Sprint 🌍 Conference Polyglot Β· Silver πŸŒ‰ Interdisciplinary Bridge Β· Silver 🐣 Hot Topic Early Bird
πŸ† Keyword Champion πŸ—ƒοΈ Keyword Collector (65) πŸ“ˆ Trend Setter πŸ’Ž Century Club Β· Bronze πŸ”₯ Unstoppable Β· Bronze 🌈 Renaissance Researcher (5)

Venues

ICML (8) NeurIPS (2) EACL (1) ICCV (1) ICLR (1)

Top co-authors

Richard Zemel (7) David Madras (4) Toniann Pitassi (3) Animesh Garg (2) Joern-Henrik Jacobsen (2) Silviu Pitis (2) Kevin Swersky (2) Ajay Mandlekar (1) Rebecca Ma (1) Yuhao Chen (1)

Research topics

Machine Learning (9) Application Areas (8) Artificial Intelligence (6) Core AI (6) Learning Types (5) Deep Learning (4) Core Methods (4) Reinforcement Learning (3) Methods (3) Data Science & Analytics (2) Architectures (2) Computer Vision (1) Robotics (1) Analysis (1) Applications (1)

Keywords

causal inference (3) counterfactual data augmentation (2) disentangled representation (2) representation learning (2) out-of-distribution generalization (2) domain adaptation (2) offline reinforcement learning (1) fairness (1) algorithmic fairness (1) model evaluation (1) sequential decision making (1) scene reconstruction (1) implicit representation (1) adversarial learning (1) distribution shift (1) model-based reinforcement learning (1) covariate shift (1) saliency map (1) off-policy reinforcement learning (1) domain generalization (1)

Papers

Say It Another Way: Auditing LLMs with a User-Grounded Automated Paraphrasing Framework EACL 2026 Out of the Ordinary: Spectrally Adapting Regression for Covariate Shift ICML 2024 Remembering to Be Fair: Non-Markovian Fairness in Sequential Decision Making ICML 2024 SurfsUP: Learning Fluid Simulation for Novel Surfaces ICCV 2023 MoCoDA: Model-based Counterfactual Data Augmentation NeurIPS 2022 Environment Inference for Invariant Learning ICML 2021 On Disentangled Representations Learned from Correlated Data ICML 2021 Causal Modeling for Fairness In Dynamical Systems ICML 2020 Counterfactual Data Augmentation using Locally Factored Dynamics NeurIPS 2020 Optimizing Long-term Social Welfare in Recommender Systems: A Constrained Matching Approach ICML 2020 Explaining Image Classifiers by Counterfactual Generation ICLR 2019 Flexibly Fair Representation Learning by Disentanglement ICML 2019 Learning Adversarially Fair and Transferable Representations ICML 2018