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Nando de Freitas

36 papers · 2003–2024 · 10 conferences · across top CS/AI conferences

Achievements

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+15 more ↓ πŸ—ΊοΈ Taxonomy Completionist (20) 🧭 Keyword Pioneer 🌈 Renaissance Researcher (7) πŸŒ‰ Interdisciplinary Bridge 🐣 Hot Topic Early Bird
🌈 Renaissance Researcher (7) πŸŒ‰ Interdisciplinary Bridge πŸƒ Academic Marathon (21) 🌟 Keyword Trendsetter Combo (3) 🀝 Dynamic Duo (13) πŸ‘‘ Triple Crown 🌱 Topic Pioneer πŸ† Keyword Champion (2) πŸ‘₯ Mega-Team (25) πŸ“ˆ Trend Setter πŸ”₯ Unstoppable (11) πŸ—ƒοΈ Keyword Collector (145) πŸš€ Conference Pioneer ⚑ Prolific Year (5) πŸ’Ž Century Club (36)

Conferences

NIPS (13) ICLR (7) ICML (4) JMLR (3) RSS (3) AISTATS (2) CORL (1) ICCV (1) IJCAI (1) INTERSPEECH (1)

Top co-authors

Misha Denil (13) Ziyu Wang (11) Caglar Gulcehre (8) Yutian Chen (8) Konrad Zolna (5) David Budden (5) Nicolas Heess (5) Thomas Paine (5) Scott Reed (5) Arnaud Doucet (5)

Keywords

reinforcement learning (4) markov random field (3) offline reinforcement learning (3) policy optimization (3) graphical model (3) probabilistic graphical model (3) batch reinforcement learning (2) deep reinforcement learning (2) generative adversarial imitation learning (2) imitation learning (2) bayesian optimization (2) multi-agent reinforcement learning (2) robotic manipulation (2) sequential decision (2) log-linear model (2) model compression (2) robot navigation (1) off-policy evaluation (1) sim-to-real transfer (1) zero-shot learning (1)

Papers

Genie: Generative Interactive Environments ICML 2024 On Instrumental Variable Regression for Deep Offline Policy Evaluation JMLR 2022 Towards Learning Universal Hyperparameter Optimizers with Transformers NIPS 2022 Active Offline Policy Selection NIPS 2021 Learning Deep Features in Instrumental Variable Regression ICLR 2021 Making Efficient Use of Demonstrations to Solve Hard Exploration Problems ICLR 2020 Scaling data-driven robotics with reward sketching and batch reinforcement learning RSS 2020 Modular Meta-Learning with Shrinkage NIPS 2020 RL Unplugged: A Suite of Benchmarks for Offline Reinforcement Learning NIPS 2020 Critic Regularized Regression NIPS 2020 Task-Relevant Adversarial Imitation Learning CORL 2020 Social Influence as Intrinsic Motivation for Multi-Agent Deep Reinforcement Learning ICML 2019 Learning Compositional Neural Programs with Recursive Tree Search and Planning NIPS 2019 Large-Scale Visual Speech Recognition INTERSPEECH 2019 Sample Efficient Adaptive Text-to-Speech ICLR 2019 Hyperbolic Attention Networks ICLR 2019 Few-shot Autoregressive Density Estimation: Towards Learning to Learn Distributions ICLR 2018 Playing hard exploration games by watching YouTube NIPS 2018 Learning Awareness Models ICLR 2018 Compositional Obverter Communication Learning from Raw Visual Input ICLR 2018 Reinforcement and Imitation Learning for Diverse Visuomotor Skills RSS 2018 Robust Imitation of Diverse Behaviors NIPS 2017 Cortical microcircuits as gated-recurrent neural networks NIPS 2017 Learning to Communicate with Deep Multi-Agent Reinforcement Learning NIPS 2016 Herded Gibbs Sampling JMLR 2016 Learning to learn by gradient descent by gradient descent NIPS 2016 Deep Fried Convnets ICCV 2015 Narrowing the Gap: Random Forests In Theory and In Practice ICML 2014 Distributed Parameter Estimation in Probabilistic Graphical Models NIPS 2014 Linear and Parallel Learning of Markov Random Fields ICML 2014 Predicting Parameters in Deep Learning NIPS 2013 Bayesian Optimization in High Dimensions via Random Embeddings IJCAI 2013 On Sparse, Spectral and Other Parameterizations of Binary Probabilistic Models AISTATS 2012 Adaptive MCMC with Bayesian Optimization AISTATS 2012 Active Policy Learning for Robot Planning and Exploration under Uncertainty RSS 2007 Matching Words and Pictures JMLR 2003