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Nando de Freitas

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Papers (71)

  1. Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models cs.LG · 2024 · author #16
  2. Reinforced Self-Training (ReST) for Language Modeling cs.CL · 2023 · author #14
  3. A Generalist Agent cs.AI · 2022 · author #20
  4. Meta-learning of Sequential Strategies cs.LG · 2019 · author #22
  5. Bayesian Optimization in AlphaGo cs.LG · 2018 · author #7
  6. Social Influence as Intrinsic Motivation for Multi-Agent Deep Reinforcement Learning cs.LG · 2018 · author #8
  7. One-Shot High-Fidelity Imitation: Training Large-Scale Deep Nets with RL cs.LG · 2018 · author #11
  8. Sample Efficient Adaptive Text-to-Speech cs.LG · 2018 · author #14
  9. Large-Scale Visual Speech Recognition cs.CV · 2018 · author #15
  10. Playing hard exploration games by watching YouTube cs.LG · 2018 · author #6
  11. Hyperbolic Attention Networks cs.NE · 2018 · author #11
  12. Learning Awareness Models cs.AI · 2018 · author #9
  13. Compositional Obverter Communication Learning From Raw Visual Input cs.AI · 2018 · author #3
  14. Reinforcement and Imitation Learning for Diverse Visuomotor Skills cs.RO · 2018 · author #10
  15. Cortical microcircuits as gated-recurrent neural networks q-bio.NC · 2017 · author #4
  16. Few-shot Autoregressive Density Estimation: Towards Learning to Learn Distributions cs.NE · 2017 · author #8
  17. The Intentional Unintentional Agent: Learning to Solve Many Continuous Control Tasks Simultaneously cs.AI · 2017 · author #6
  18. Robust Imitation of Diverse Behaviors cs.LG · 2017 · author #5
  19. Programmable Agents cs.AI · 2017 · author #5
  20. Learned Optimizers that Scale and Generalize cs.LG · 2017 · author #6
  21. Parallel Multiscale Autoregressive Density Estimation cs.CV · 2017 · author #7
  22. Learning to Learn without Gradient Descent by Gradient Descent stat.ML · 2016 · author #7
  23. Learning to Perform Physics Experiments via Deep Reinforcement Learning stat.ML · 2016 · author #6
  24. LipNet: End-to-End Sentence-level Lipreading cs.LG · 2016 · author #4
  25. Sample Efficient Actor-Critic with Experience Replay cs.LG · 2016 · author #7
  26. Learning to learn by gradient descent by gradient descent cs.NE · 2016 · author #8
  27. Learning to Communicate with Deep Multi-Agent Reinforcement Learning cs.AI · 2016 · author #3
  28. Learning to Communicate to Solve Riddles with Deep Distributed Recurrent Q-Networks cs.AI · 2016 · author #3
  29. Dueling Network Architectures for Deep Reinforcement Learning cs.LG · 2015 · author #6
  30. Neural Programmer-Interpreters cs.LG · 2015 · author #2
  31. ACDC: A Structured Efficient Linear Layer cs.LG · 2015 · author #4
  32. Unbounded Bayesian Optimization via Regularization stat.ML · 2015 · author #3
  33. Deep Fried Convnets cs.LG · 2014 · author #4
  34. Extraction of Salient Sentences from Labelled Documents cs.CL · 2014 · author #3
  35. Deep Multi-Instance Transfer Learning cs.LG · 2014 · author #4
  36. Heteroscedastic Treed Bayesian Optimisation cs.LG · 2014 · author #4
  37. Theoretical Analysis of Bayesian Optimisation with Unknown Gaussian Process Hyper-Parameters stat.ML · 2014 · author #2
  38. An Entropy Search Portfolio for Bayesian Optimization stat.ML · 2014 · author #5
  39. Modelling, Visualising and Summarising Documents with a Single Convolutional Neural Network cs.CL · 2014 · author #5
  40. Distributed Parameter Estimation in Probabilistic Graphical Models stat.ML · 2014 · author #3
  41. A Deep Architecture for Semantic Parsing cs.CL · 2014 · author #3
  42. Bayesian Multi-Scale Optimistic Optimization stat.ML · 2014 · author #4
  43. Narrowing the Gap: Random Forests In Theory and In Practice stat.ML · 2013 · author #3
  44. Linear and Parallel Learning of Markov Random Fields stat.ML · 2013 · author #3
  45. Predicting Parameters in Deep Learning cs.LG · 2013 · author #5
  46. Exploiting correlation and budget constraints in Bayesian multi-armed bandit optimization stat.ML · 2013 · author #3
  47. Adaptive Hamiltonian and Riemann Manifold Monte Carlo Samplers stat.CO · 2013 · author #3
  48. Consistency of Online Random Forests stat.ML · 2013 · author #3
  49. Proceedings of the Twenty-Eighth Conference on Uncertainty in Artificial Intelligence (2012) cs.AI · 2013 · author #1
  50. Herded Gibbs Sampling cs.LG · 2013 · author #3
  51. Rao-Blackwellised Particle Filtering for Dynamic Bayesian Networks cs.LG · 2013 · author #2
  52. Reversible Jump MCMC Simulated Annealing for Neural Networks cs.LG · 2013 · author #2
  53. Variational MCMC cs.LG · 2013 · author #1
  54. Bayesian Optimization in a Billion Dimensions via Random Embeddings stat.ML · 2013 · author #5
  55. Recklessly Approximate Sparse Coding cs.LG · 2012 · author #2
  56. From Fields to Trees stat.CO · 2012 · author #2
  57. Toward Practical N2 Monte Carlo: the Marginal Particle Filter stat.CO · 2012 · author #2
  58. Learning about individuals from group statistics cs.LG · 2012 · author #2
  59. Nonparametric Bayesian Logic cs.AI · 2012 · author #3
  60. Large-Flip Importance Sampling stat.CO · 2012 · author #2
  61. New inference strategies for solving Markov Decision Processes using reversible jump MCMC cs.LG · 2012 · author #3
  62. Intracluster Moves for Constrained Discrete-Space MCMC stat.CO · 2012 · author #2
  63. Decentralized, Adaptive, Look-Ahead Particle Filtering stat.ML · 2012 · author #3
  64. Regret Bounds for Deterministic Gaussian Process Bandits cs.LG · 2012 · author #1
  65. Asymptotic Efficiency of Deterministic Estimators for Discrete Energy-Based Models: Ratio Matching and Pseudolikelihood cs.LG · 2012 · author #2
  66. Self-Avoiding Random Dynamics on Integer Complex Systems stat.CO · 2011 · author #3
  67. Bayesian Optimization for Adaptive MCMC stat.CO · 2011 · author #4
  68. Learning where to Attend with Deep Architectures for Image Tracking cs.AI · 2011 · author #4
  69. A Machine Learning Perspective on Predictive Coding with PAQ cs.LG · 2011 · author #2
  70. A Tutorial on Bayesian Optimization of Expensive Cost Functions, with Application to Active User Modeling and Hierarchical Reinforcement Learning cs.LG · 2010 · author #3
  71. Portfolio Allocation for Bayesian Optimization cs.LG · 2010 · author #3

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