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Clare Lyle

23 papers · 2019–2025 · 6 venues · across top CS/AI venues

Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.

Achievements

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+8 more ↓ πŸ—ΊοΈ Taxonomy Completionist (36) 🌍 Conference Polyglot Β· Silver πŸƒ Academic Marathon Β· Sprint πŸŒ‰ Interdisciplinary Bridge Β· Bronze 🐣 Hot Topic Early Bird
🀝 Dynamic Duo (12) πŸ† Grand Slam πŸ”¬ Deep Specialist (14) ⚑ Prolific Year Β· Productive πŸ”₯ Unstoppable Β· Bronze πŸ’Ž Century Club Β· Bronze πŸš€ Conference Pioneer πŸ—ƒοΈ Keyword Collector (109)

Venues

ICML (10) NeurIPS (8) AISTATS (2) AAAI (1) ICLR (1) IJCAI (1)

Top co-authors

Will Dabney (12) Mark Rowland (8) Yarin Gal (7) Yunhao Tang (5) RΓ©mi Munos (4) Razvan Pascanu (4) Pablo Samuel Castro (3) Georg Ostrovski (3) Marta Kwiatkowska (3) Bernardo Avila Pires (3)

Research topics

Machine Learning (20) Reinforcement Learning (14) Methods (14) Optimization & Theory (12) Artificial Intelligence (8) Deep Learning (7) Core AI (7) Core Methods (7) Learning Types Β· Machine Learning (7) Learning Types Β· Deep Learning (4) Architectures (3) Application Areas (2) Applications (2) Learning Paradigms (2) Knowledge & Reasoning (1)

Keywords

reinforcement learning (6) distributional reinforcement learning (4) deep reinforcement learning (4) representation learning (3) neural network (3) continual learning (2) causal inference (2) return distribution (2) neural network plasticity (2) auxiliary task (2) spectral decomposition (2) value function (2) temporal difference learning (2) value estimation (2) sparse reward (2) bayesian inference (1) imitation learning (1) model selection (1) self-attention mechanism (1) state abstraction (1)

Papers

A Unifying Framework for Action-Conditional Self-Predictive Reinforcement Learning AISTATS 2025 Mixtures of Experts Unlock Parameter Scaling for Deep RL ICML 2024 Near-Minimax-Optimal Distributional Reinforcement Learning with a Generative Model NeurIPS 2024 Non-Stationary Learning of Neural Networks with Automatic Soft Parameter Reset NeurIPS 2024 Normalization and effective learning rates in reinforcement learning NeurIPS 2024 Slow and Steady Wins the Race: Maintaining Plasticity with Hare and Tortoise Networks ICML 2024 Deep Reinforcement Learning with Plasticity Injection NeurIPS 2023 DiscoBAX: Discovery of optimal intervention sets in genomic experiment design ICML 2023 Quantile Credit Assignment ICML 2023 The Statistical Benefits of Quantile Temporal-Difference Learning for Value Estimation ICML 2023 Understanding Plasticity in Neural Networks ICML 2023 Understanding Self-Predictive Learning for Reinforcement Learning ICML 2023 Learning Dynamics and Generalization in Deep Reinforcement Learning ICML 2022 Understanding and Preventing Capacity Loss in Reinforcement Learning ICLR 2022 On the Effect of Auxiliary Tasks on Representation Dynamics AISTATS 2021 Provable Guarantees on the Robustness of Decision Rules to Causal Interventions IJCAI 2021 PsiPhi-Learning: Reinforcement Learning with Demonstrations using Successor Features and Inverse Temporal Difference Learning ICML 2021 Self-Attention Between Datapoints: Going Beyond Individual Input-Output Pairs in Deep Learning NeurIPS 2021 Speedy Performance Estimation for Neural Architecture Search NeurIPS 2021 A Bayesian Perspective on Training Speed and Model Selection NeurIPS 2020 Invariant Causal Prediction for Block MDPs ICML 2020 A Comparative Analysis of Expected and Distributional Reinforcement Learning AAAI 2019 A Geometric Perspective on Optimal Representations for Reinforcement Learning NeurIPS 2019