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Nando de Freitas

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

Achievements

🐝 Cross-Pollinator (14) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🌍 Conference Polyglot (10) πŸ—ΊοΈ Taxonomy Completionist (20) 🌈 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