de Freitas, Nando

74 publications

ICML 2024 Genie: Generative Interactive Environments Jake Bruce, Michael D Dennis, Ashley Edwards, Jack Parker-Holder, Yuge Shi, Edward Hughes, Matthew Lai, Aditi Mavalankar, Richie Steigerwald, Chris Apps, Yusuf Aytar, Sarah Maria Elisabeth Bechtle, Feryal Behbahani, Stephanie C.Y. Chan, Nicolas Heess, Lucy Gonzalez, Simon Osindero, Sherjil Ozair, Scott Reed, Jingwei Zhang, Konrad Zolna, Jeff Clune, Nando De Freitas, Satinder Singh, Tim Rocktäschel

ICLRW 2023 Knowledge Transfer from Teachers to Learners in Growing-Batch Reinforcement Learning Patrick Emedom-Nnamdi, Abram L. Friesen, Bobak Shahriari, Nando de Freitas, Matthew Hoffman

TMLR 2022 A Generalist Agent Scott Reed, Konrad Zolna, Emilio Parisotto, Sergio Gómez Colmenarejo, Alexander Novikov, Gabriel Barth-maron, Mai Giménez, Yury Sulsky, Jackie Kay, Jost Tobias Springenberg, Tom Eccles, Jake Bruce, Ali Razavi, Ashley Edwards, Nicolas Heess, Yutian Chen, Raia Hadsell, Oriol Vinyals, Mahyar Bordbar, Nando de Freitas

NeurIPSW 2022 Multi-Step Planning for Automated Hyperparameter Optimization with OptFormer Lucio M. Dery, Abram L. Friesen, Nando de Freitas, MarcAurelio Ranzato, Yutian Chen

JMLR 2022 On Instrumental Variable Regression for Deep Offline Policy Evaluation Yutian Chen, Liyuan Xu, Caglar Gulcehre, Tom Le Paine, Arthur Gretton, Nando de Freitas, Arnaud Doucet

NeurIPS 2022 Towards Learning Universal Hyperparameter Optimizers with Transformers Yutian Chen, Xingyou Song, Chansoo Lee, Zi Wang, Richard Zhang, David Dohan, Kazuya Kawakami, Greg Kochanski, Arnaud Doucet, Marc'Aurelio Ranzato, Sagi Perel, Nando de Freitas

NeurIPS 2021 Active Offline Policy Selection Ksenia Konyushova, Yutian Chen, Thomas Paine, Caglar Gulcehre, Cosmin Paduraru, Daniel J Mankowitz, Misha Denil, Nando de Freitas

ICLR 2021 Learning Deep Features in Instrumental Variable Regression Liyuan Xu, Yutian Chen, Siddarth Srinivasan, Nando de Freitas, Arnaud Doucet, Arthur Gretton

NeurIPSW 2021 StarCraft II Unplugged: Large Scale Offline Reinforcement Learning Michael Mathieu, Sherjil Ozair, Srivatsan Srinivasan, Caglar Gulcehre, Shangtong Zhang, Ray Jiang, Tom Le Paine, Konrad Zolna, Richard Powell, Julian Schrittwieser, David Choi, Petko Georgiev, Daniel Kenji Toyama, Aja Huang, Roman Ring, Igor Babuschkin, Timo Ewalds, Mahyar Bordbar, Sarah Henderson, Sergio Gómez Colmenarejo, Aaron van den Oord, Wojciech M. Czarnecki, Nando de Freitas, Oriol Vinyals

NeurIPS 2020 Critic Regularized Regression Ziyu Wang, Alexander Novikov, Konrad Zolna, Josh S Merel, Jost Tobias Springenberg, Scott E Reed, Bobak Shahriari, Noah Siegel, Caglar Gulcehre, Nicolas Heess, Nando de Freitas

ICLR 2020 Making Efficient Use of Demonstrations to Solve Hard Exploration Problems Tom Le Paine, Caglar Gulcehre, Bobak Shahriari, Misha Denil, Matt Hoffman, Hubert Soyer, Richard Tanburn, Steven Kapturowski, Neil Rabinowitz, Duncan Williams, Gabriel Barth-Maron, Ziyu Wang, Nando de Freitas, Worlds Team

NeurIPS 2020 Modular Meta-Learning with Shrinkage Yutian Chen, Abram L. Friesen, Feryal Behbahani, Arnaud Doucet, David Budden, Matthew Hoffman, Nando de Freitas

NeurIPS 2020 RL Unplugged: A Suite of Benchmarks for Offline Reinforcement Learning Caglar Gulcehre, Ziyu Wang, Alexander Novikov, Thomas Paine, Sergio Gómez, Konrad Zolna, Rishabh Agarwal, Josh S Merel, Daniel J Mankowitz, Cosmin Paduraru, Gabriel Dulac-Arnold, Jerry Li, Mohammad Norouzi, Matthew Hoffman, Nicolas Heess, Nando de Freitas

CoRL 2020 Task-Relevant Adversarial Imitation Learning Konrad Zolna, Scott Reed, Alexander Novikov, Sergio Gómez Colmenarejo, David Budden, Serkan Cabi, Misha Denil, Nando de Freitas, Ziyu Wang

ICLR 2019 Hyperbolic Attention Networks Caglar Gulcehre, Misha Denil, Mateusz Malinowski, Ali Razavi, Razvan Pascanu, Karl Moritz Hermann, Peter Battaglia, Victor Bapst, David Raposo, Adam Santoro, Nando de Freitas

NeurIPS 2019 Learning Compositional Neural Programs with Recursive Tree Search and Planning Thomas Pierrot, Guillaume Ligner, Scott E Reed, Olivier Sigaud, Nicolas Perrin, Alexandre Laterre, David Kas, Karim Beguir, Nando de Freitas

ICLR 2019 Sample Efficient Adaptive Text-to-Speech Yutian Chen, Yannis Assael, Brendan Shillingford, David Budden, Scott Reed, Heiga Zen, Quan Wang, Luis C. Cobo, Andrew Trask, Ben Laurie, Caglar Gulcehre, Aäron van den Oord, Oriol Vinyals, Nando de Freitas

ICML 2019 Social Influence as Intrinsic Motivation for Multi-Agent Deep Reinforcement Learning Natasha Jaques, Angeliki Lazaridou, Edward Hughes, Caglar Gulcehre, Pedro Ortega, Dj Strouse, Joel Z. Leibo, Nando De Freitas

ICLR 2018 Compositional Obverter Communication Learning from Raw Visual Input Edward Choi, Angeliki Lazaridou, Nando de Freitas

ICLR 2018 Few-Shot Autoregressive Density Estimation: Towards Learning to Learn Distributions Scott Reed, Yutian Chen, Thomas Paine, Aäron van den Oord, S. M. Ali Eslami, Danilo Rezende, Oriol Vinyals, Nando de Freitas

ICLR 2018 Learning Awareness Models Brandon Amos, Laurent Dinh, Serkan Cabi, Thomas Rothörl, Sergio Gómez Colmenarejo, Alistair Muldal, Tom Erez, Yuval Tassa, Nando de Freitas, Misha Denil

NeurIPS 2018 Playing Hard Exploration Games by Watching YouTube Yusuf Aytar, Tobias Pfaff, David Budden, Thomas Paine, Ziyu Wang, Nando de Freitas

NeurIPS 2017 Cortical Microcircuits as Gated-Recurrent Neural Networks Rui Costa, Ioannis Alexandros Assael, Brendan Shillingford, Nando de Freitas, TIm Vogels

ICLR 2017 Learning to Perform Physics Experiments via Deep Reinforcement Learning Misha Denil, Pulkit Agrawal, Tejas D. Kulkarni, Tom Erez, Peter W. Battaglia, Nando de Freitas

NeurIPS 2017 Robust Imitation of Diverse Behaviors Ziyu Wang, Josh S Merel, Scott E Reed, Nando de Freitas, Gregory Wayne, Nicolas Heess

ICLR 2017 Sample Efficient Actor-Critic with Experience Replay Ziyu Wang, Victor Bapst, Nicolas Heess, Volodymyr Mnih, Rémi Munos, Koray Kavukcuoglu, Nando de Freitas

CoRL 2017 The Intentional Unintentional Agent: Learning to Solve Many Continuous Control Tasks Simultaneously Serkan Cabi, Sergio Gomez Colmenarejo, Matthew W. Hoffman, Misha Denil, Ziyu Wang, Nando de Freitas

ICLR 2016 ACDC: A Structured Efficient Linear Layer Marcin Moczulski, Misha Denil, Jeremy Appleyard, Nando de Freitas

JAIR 2016 Bayesian Optimization in a Billion Dimensions via Random Embeddings Ziyu Wang, Frank Hutter, Masrour Zoghi, David Matheson, Nando de Freitas

JMLR 2016 Herded Gibbs Sampling Yutian Chen, Luke Bornn, Nando de Freitas, Mareija Eskelin, Jing Fang, Max Welling

NeurIPS 2016 Learning to Communicate with Deep Multi-Agent Reinforcement Learning Jakob Foerster, Ioannis Alexandros Assael, Nando de Freitas, Shimon Whiteson

NeurIPS 2016 Learning to Learn by Gradient Descent by Gradient Descent Marcin Andrychowicz, Misha Denil, Sergio Gómez, Matthew W Hoffman, David Pfau, Tom Schaul, Brendan Shillingford, Nando de Freitas

ICLR 2016 Neural Programmer-Interpreters Scott E. Reed, Nando de Freitas

AISTATS 2016 Unbounded Bayesian Optimization via Regularization Bobak Shahriari, Alexandre Bouchard-Côté, Nando de Freitas

ICCV 2015 Deep Fried Convnets Zichao Yang, Marcin Moczulski, Misha Denil, Nando de Freitas, Alex Smola, Le Song, Ziyu Wang

AISTATS 2014 Bayesian Multi-Scale Optimistic Optimization Ziyu Wang, Babak Shakibi, Lin Jin, Nando de Freitas

WACV 2014 Bayesian Optimization with an Empirical Hardness Model for Approximate Nearest Neighbour Search Julieta Martinez, James J. Little, Nando de Freitas

NeurIPS 2014 Distributed Parameter Estimation in Probabilistic Graphical Models Yariv D Mizrahi, Misha Denil, Nando de Freitas

ICML 2014 Linear and Parallel Learning of Markov Random Fields Yariv Mizrahi, Misha Denil, Nando De Freitas

ICML 2014 Narrowing the Gap: Random Forests in Theory and in Practice Misha Denil, David Matheson, Nando De Freitas

AISTATS 2014 On Correlation and Budget Constraints in Model-Based Bandit Optimization with Application to Automatic Machine Learning Matthew W. Hoffman, Bobak Shahriari, Nando de Freitas

IJCAI 2013 Bayesian Optimization in High Dimensions via Random Embeddings Ziyu Wang, Masrour Zoghi, Frank Hutter, David Matheson, Nando de Freitas

ICLR 2013 Herded Gibbs Sampling Luke Bornn, Yutian Chen, Nando de Freitas, Mareija Eskelin, Jing Fang, Max Welling

NeurIPS 2013 Predicting Parameters in Deep Learning Misha Denil, Babak Shakibi, Laurent Dinh, Marc'Aurelio Ranzato, Nando de Freitas

AISTATS 2012 Adaptive MCMC with Bayesian Optimization Nimalan Mahendran, Ziyu Wang, Firas Hamze, Nando De Freitas

ICML 2012 Exponential Regret Bounds for Gaussian Process Bandits with Deterministic Observations Nando de Freitas, Alexander J. Smola, Masrour Zoghi

AISTATS 2012 On Sparse, Spectral and Other Parameterizations of Binary Probabilistic Models David Buchman, Mark Schmidt, Shakir Mohamed, David Poole, Nando De Freitas

AAAI 2012 Prediction and Fault Detection of Environmental Signals with Uncharacterised Faults Michael A. Osborne, Roman Garnett, Kevin Swersky, Nando de Freitas

UAI 2012 Proceedings of the Twenty-Eighth Conference on Uncertainty in Artificial Intelligence, Catalina Island, CA, USA, August 14-18, 2012 Nando de Freitas, Kevin P. Murphy

UAI 2011 Asymptotic Efficiency of Deterministic Estimators for Discrete Energy-Based Models: Ratio Matching and Pseudolikelihood Benjamin M. Marlin, Nando de Freitas

ICML 2011 Learning Attentional Policies for Tracking and Recognition in Video with Deep Networks Loris Bazzani, Nando de Freitas, Hugo Larochelle, Vittorio Murino, Jo-Anne Ting

ICML 2011 On Autoencoders and Score Matching for Energy Based Models Kevin Swersky, Marc'Aurelio Ranzato, David Buchman, Benjamin M. Marlin, Nando de Freitas

UAI 2011 Portfolio Allocation for Bayesian Optimization Matthew Hoffman, Eric Brochu, Nando de Freitas

UAI 2010 Intracluster Moves for Constrained Discrete-Space MCMC Firas Hamze, Nando de Freitas

UAI 2009 New Inference Strategies for Solving Markov Decision Processes Using Reversible Jump MCMC Matthias Hoffman, Hendrik Kück, Nando de Freitas, Arnaud Doucet

UAI 2007 Large-Flip Importance Sampling Firas Hamze, Nando de Freitas

ICML 2006 Fast Particle Smoothing: If I Had a Million Particles Mike Klaas, Mark Briers, Nando de Freitas, Arnaud Doucet, Simon Maskell, Dustin Lang

ECCV 2006 Robust Visual Tracking for Multiple Targets Yizheng Cai, Nando de Freitas, James J. Little

NeurIPS 2005 Hot Coupling: A Particle Approach to Inference and Normalization on Pairwise Undirected Graphs Firas Hamze, Nando de Freitas

UAI 2005 Learning About Individuals from Group Statistics Nando de Freitas, Hendrik Kück

UAI 2005 Nonparametric Bayesian Logic Peter Carbonetto, Jacek Kisynski, Nando de Freitas, David Poole

UAI 2005 Toward Practical N2 Monte Carlo: The Marginal Particle Filter Mike Klaas, Nando de Freitas, Arnaud Doucet

ECCV 2004 A Boosted Particle Filter: Multitarget Detection and Tracking Kenji Okuma, Ali Taleghani, Nando de Freitas, James J. Little, David G. Lowe

ECCV 2004 A Constrained Semi-Supervised Learning Approach to Data Association Hendrik Kück, Peter Carbonetto, Nando de Freitas

ECCV 2004 A Statistical Model for General Contextual Object Recognition Peter Carbonetto, Nando de Freitas, Kobus Barnard

UAI 2004 From Fields to Trees Firas Hamze, Nando de Freitas

MLJ 2003 An Introduction to MCMC for Machine Learning Christophe Andrieu, Nando de Freitas, Arnaud Doucet, Michael I. Jordan

NeurIPS 2002 "Name That Song!" a Probabilistic Approach to Querying on Music and Text Brochu Eric, Nando de Freitas

NeurIPS 2002 Real-Time Monitoring of Complex Industrial Processes with Particle Filters Rubén Morales-Menéndez, Nando de Freitas, David Poole

NeCo 2001 Robust Full Bayesian Learning for Radial Basis Networks Christophe Andrieu, Nando de Freitas, Arnaud Doucet

UAI 2001 Variational MCMC Nando de Freitas, Pedro A. d. F. R. Højen-Sørensen, Stuart Russell

UAI 2000 Rao-Blackwellised Particle Filtering for Dynamic Bayesian Networks Arnaud Doucet, Nando de Freitas, Kevin P. Murphy, Stuart Russell

UAI 2000 Reversible Jump MCMC Simulated Annealing for Neural Networks Christophe Andrieu, Nando de Freitas, Arnaud Doucet

NeurIPS 2000 The Unscented Particle Filter Rudolph van der Merwe, Arnaud Doucet, Nando de Freitas, Eric A. Wan