Rein Houthooft

7 papers · 2016–2018 · 3 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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🌍 Conference Polyglot · Bronze 🌉 Interdisciplinary Bridge · Bronze 🗺️ Taxonomy Completionist (10) 🐣 Hot Topic Early Bird 🚀 Conference Pioneer

Venues

NeurIPS (5) ICLR (1) ICML (1)

Top co-authors

Pieter Abbeel (7) Yan Duan (5) Xi Chen (4) John Schulman (4) Ilya Sutskever (2) Filip De Turck (2) Bradly Stadie (2) Haoran Tang (1) Tamim Asfour (1) Adam Stooke (1)

Research topics

Reinforcement Learning (6) Methods (6) Artificial Intelligence (3) Deep Learning (2) Machine Learning (2) Core AI (2) Learning Paradigms (2) Learning Types · Deep Learning (2) Applications (1) Core Methods (1) Learning Types · Machine Learning (1) Optimization & Theory (1)

Keywords

deep reinforcement learning (3) policy gradient (2) exploration bonus (2) continuous control (2) intrinsic motivation (2) out-of-distribution generalization (1) sampling distribution (1) mutual information (1) state space exploration (1) off-policy learning (1) disentangled representation (1) generative adversarial network (1) meta-reinforcement learning (1) tabular reinforcement learning (1) on-policy learning (1) evolutionary algorithm (1) bayesian neural network (1) hash table (1) temporal convolution (1) efficient learning (1)

Papers

Evolved Policy Gradients NeurIPS 2018 Parameter Space Noise for Exploration ICLR 2018 The Importance of Sampling inMeta-Reinforcement Learning NeurIPS 2018 #Exploration: A Study of Count-Based Exploration for Deep Reinforcement Learning NeurIPS 2017 Benchmarking Deep Reinforcement Learning for Continuous Control ICML 2016 InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets NeurIPS 2016 VIME: Variational Information Maximizing Exploration NeurIPS 2016