Nando de Freitas

Publication Activity (10 Years)

Years Active: 2000-2024
Publications (10 Years): 96

Top Venues

CoRR

ICLR (Poster)

ICML

NeurIPS

Publications

Soham De, Samuel L. Smith, Anushan Fernando, Aleksandar Botev, George-Cristian Muraru, Albert Gu, Ruba Haroun, Leonard Berrada, Yutian Chen, Srivatsan Srinivasan, Guillaume Desjardins, Arnaud Doucet, David Budden, Yee Whye Teh, Razvan Pascanu, Nando de Freitas, Caglar Gulcehre
Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models. CoRR (2024)
Jake Bruce, Michael Dennis, Ashley Edwards, Jack Parker-Holder, Yuge Shi, Edward Hughes, Matthew Lai, Aditi Mavalankar, Richie Steigerwald, Chris Apps, Yusuf Aytar, Sarah Bechtle, Feryal M. P. Behbahani, Stephanie C. Y. Chan, Nicolas Heess, Lucy Gonzalez, Simon Osindero, Sherjil Ozair, Scott E. Reed, Jingwei Zhang, Konrad Zolna, Jeff Clune, Nando de Freitas, Satinder Singh, Tim Rocktäschel
Genie: Generative Interactive Environments. CoRR (2024)
Patrick Emedom-Nnamdi, Abram L. Friesen, Bobak Shahriari, Nando de Freitas, Matthew W. Hoffman
Knowledge Transfer from Teachers to Learners in Growing-Batch Reinforcement Learning. CoRR (2023)
Yuqing Du, Ksenia Konyushkova, Misha Denil, Akhil Raju, Jessica Landon, Felix Hill, Nando de Freitas, Serkan Cabi
Vision-Language Models as Success Detectors. CoLLAs (2023)
Thea Sommerschield, Yannis M. Assael, John Pavlopoulos, Vanessa Stefanak, Andrew W. Senior, Chris Dyer, John Bodel, Jonathan Prag, Ion Androutsopoulos, Nando de Freitas
Machine Learning for Ancient Languages: A Survey. Comput. Linguistics 49 (3) (2023)
Michaël Mathieu, Sherjil Ozair, Srivatsan Srinivasan, Çaglar Gülçehre, Shangtong Zhang, Ray Jiang, Tom Le Paine, Richard Powell, Konrad Zolna, Julian Schrittwieser, David H. Choi, Petko Georgiev, Daniel Toyama, Aja Huang, Roman Ring, Igor Babuschkin, Timo Ewalds, Mahyar Bordbar, Sarah Henderson, Sergio Gómez Colmenarejo, Aäron van den Oord, Wojciech Marian Czarnecki, Nando de Freitas, Oriol Vinyals
AlphaStar Unplugged: Large-Scale Offline Reinforcement Learning. CoRR (2023)
Çaglar Gülçehre, Tom Le Paine, Srivatsan Srinivasan, Ksenia Konyushkova, Lotte Weerts, Abhishek Sharma, Aditya Siddhant, Alex Ahern, Miaosen Wang, Chenjie Gu, Wolfgang Macherey, Arnaud Doucet, Orhan Firat, Nando de Freitas
Reinforced Self-Training (ReST) for Language Modeling. CoRR (2023)
Yuqing Du, Ksenia Konyushkova, Misha Denil, Akhil Raju, Jessica Landon, Felix Hill, Nando de Freitas, Serkan Cabi
Vision-Language Models as Success Detectors. CoRR (2023)
Yutian Chen, Liyuan Xu, Çaglar Gülçehre, Tom Le Paine, Arthur Gretton, Nando de Freitas, Arnaud Doucet
On Instrumental Variable Regression for Deep Offline Policy Evaluation. J. Mach. Learn. Res. 23 (2022)
Lucio M. Dery, Abram L. Friesen, Nando de Freitas, Marc'Aurelio Ranzato, Yutian Chen
Multi-step Planning for Automated Hyperparameter Optimization with OptFormer. CoRR (2022)
Yannis M. Assael, Thea Sommerschield, Brendan Shillingford, Mahyar Bordbar, John Pavlopoulos, Marita Chatzipanagiotou, Ion Androutsopoulos, Jonathan Prag, Nando de Freitas
Restoring and attributing ancient texts using deep neural networks. Nat. 603 (7900) (2022)
Scott E. Reed, Konrad Zolna, Emilio Parisotto, Sergio Gómez Colmenarejo, Alexander Novikov, Gabriel Barth-Maron, Mai Gimenez, 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
A Generalist Agent. Trans. Mach. Learn. Res. 2022 (2022)
Yutian Chen, Xingyou Song, Chansoo Lee, Zi Wang, Qiuyi Zhang, David Dohan, Kazuya Kawakami, Greg Kochanski, Arnaud Doucet, Marc'Aurelio Ranzato, Sagi Perel, Nando de Freitas
Towards Learning Universal Hyperparameter Optimizers with Transformers. CoRR (2022)
Scott E. Reed, Konrad Zolna, Emilio Parisotto, Sergio Gomez Colmenarejo, Alexander Novikov, Gabriel Barth-Maron, Mai Gimenez, 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
A Generalist Agent. CoRR (2022)
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
Towards Learning Universal Hyperparameter Optimizers with Transformers. NeurIPS (2022)
Yujia Li, David H. Choi, Junyoung Chung, Nate Kushman, Julian Schrittwieser, Rémi Leblond, Tom Eccles, James Keeling, Felix Gimeno, Agustin Dal Lago, Thomas Hubert, Peter Choy, Cyprien de Masson d'Autume, Igor Babuschkin, Xinyun Chen, Po-Sen Huang, Johannes Welbl, Sven Gowal, Alexey Cherepanov, James Molloy, Daniel J. Mankowitz, Esme Sutherland Robson, Pushmeet Kohli, Nando de Freitas, Koray Kavukcuoglu, Oriol Vinyals
Competition-Level Code Generation with AlphaCode. CoRR (2022)
Yutian Chen, Liyuan Xu, Çaglar Gülçehre, Tom Le Paine, Arthur Gretton, Nando de Freitas, Arnaud Doucet
On Instrumental Variable Regression for Deep Offline Policy Evaluation. CoRR (2021)
Pedro A. Ortega, Markus Kunesch, Grégoire Delétang, Tim Genewein, Jordi Grau-Moya, Joel Veness, Jonas Buchli, Jonas Degrave, Bilal Piot, Julien Pérolat, Tom Everitt, Corentin Tallec, Emilio Parisotto, Tom Erez, Yutian Chen, Scott E. Reed, Marcus Hutter, Nando de Freitas, Shane Legg
Shaking the foundations: delusions in sequence models for interaction and control. CoRR (2021)
Ksenia Konyushkova, Yutian Chen, Thomas Paine, Çaglar Gülçehre, Cosmin Paduraru, Daniel J. Mankowitz, Misha Denil, Nando de Freitas
Active Offline Policy Selection. NeurIPS (2021)
Ksenia Konyushkova, Yutian Chen, Thomas Paine, Çaglar Gülçehre, Cosmin Paduraru, Daniel J. Mankowitz, Misha Denil, Nando de Freitas
Active Offline Policy Selection. CoRR (2021)
Liyuan Xu, Yutian Chen, Siddarth Srinivasan, Nando de Freitas, Arnaud Doucet, Arthur Gretton
Learning Deep Features in Instrumental Variable Regression. ICLR (2021)
Çaglar Gülçehre, Sergio Gómez Colmenarejo, Ziyu Wang, Jakub Sygnowski, Thomas Paine, Konrad Zolna, Yutian Chen, Matthew W. Hoffman, Razvan Pascanu, Nando de Freitas
Regularized Behavior Value Estimation. CoRR (2021)
Çaglar Gülçehre, Tom Le Paine, Bobak Shahriari, Misha Denil, Matt Hoffman, Hubert Soyer, Richard Tanburn, Steven Kapturowski, Neil C. Rabinowitz, Duncan Williams, Gabriel Barth-Maron, Ziyu Wang, Nando de Freitas, Worlds Team
Making Efficient Use of Demonstrations to Solve Hard Exploration Problems. ICLR (2020)
Serkan Cabi, Sergio Gómez Colmenarejo, Alexander Novikov, Ksenia Konyushkova, Scott E. Reed, Rae Jeong, Konrad Zolna, Yusuf Aytar, David Budden, Mel Vecerík, Oleg Sushkov, David Barker, Jonathan Scholz, Misha Denil, Nando de Freitas, Ziyu Wang
Scaling data-driven robotics with reward sketching and batch reinforcement learning. Robotics: Science and Systems (2020)
Yi Yang, Brendan Shillingford, Yannis M. Assael, Miaosen Wang, Wendi Liu, Yutian Chen, Yu Zhang, Eren Sezener, Luis C. Cobo, Misha Denil, Yusuf Aytar, Nando de Freitas
Large-scale multilingual audio visual dubbing. CoRR (2020)
Çaglar Gülçehre, Ziyu Wang, Alexander Novikov, Thomas Paine, Sergio Gómez Colmenarejo, Konrad Zolna, Rishabh Agarwal, Josh Merel, Daniel J. Mankowitz, Cosmin Paduraru, Gabriel Dulac-Arnold, Jerry Li, Mohammad Norouzi, Matthew Hoffman, Nicolas Heess, Nando de Freitas
RL Unplugged: A Collection of Benchmarks for Offline Reinforcement Learning. NeurIPS (2020)
Tom Le Paine, Cosmin Paduraru, Andrea Michi, Çaglar Gülçehre, Konrad Zolna, Alexander Novikov, Ziyu Wang, Nando de Freitas
Hyperparameter Selection for Offline Reinforcement Learning. CoRR (2020)
Thomas Pierrot, Nicolas Perrin, Feryal Behbahani, Alexandre Laterre, Olivier Sigaud, Karim Beguir, Nando de Freitas
Learning Compositional Neural Programs for Continuous Control. CoRR (2020)
Konrad Zolna, Alexander Novikov, Ksenia Konyushkova, Çaglar Gülçehre, Ziyu Wang, Yusuf Aytar, Misha Denil, Nando de Freitas, Scott E. Reed
Offline Learning from Demonstrations and Unlabeled Experience. CoRR (2020)
Çaglar Gülçehre, Ziyu Wang, Alexander Novikov, Tom Le Paine, Sergio Gómez Colmenarejo, Konrad Zolna, Rishabh Agarwal, Josh Merel, Daniel J. Mankowitz, Cosmin Paduraru, Gabriel Dulac-Arnold, Jerry Li, Mohammad Norouzi, Matt Hoffman, Ofir Nachum, George Tucker, Nicolas Heess, Nando de Freitas
RL Unplugged: Benchmarks for Offline Reinforcement Learning. CoRR (2020)
Yutian Chen, Abram L. Friesen, Feryal Behbahani, Arnaud Doucet, David Budden, Matthew Hoffman, Nando de Freitas
Modular Meta-Learning with Shrinkage. NeurIPS (2020)
Ziyu Wang, Alexander Novikov, Konrad Zolna, Josh Merel, Jost Tobias Springenberg, Scott E. Reed, Bobak Shahriari, Noah Y. Siegel, Çaglar Gülçehre, Nicolas Heess, Nando de Freitas
Critic Regularized Regression. NeurIPS (2020)
Ziyu Wang, Alexander Novikov, Konrad Zolna, Jost Tobias Springenberg, Scott E. Reed, Bobak Shahriari, Noah Y. Siegel, Josh Merel, Çaglar Gülçehre, Nicolas Heess, Nando de Freitas
Critic Regularized Regression. CoRR (2020)
Liyuan Xu, Yutian Chen, Siddarth Srinivasan, Nando de Freitas, Arnaud Doucet, Arthur Gretton
Learning Deep Features in Instrumental Variable Regression. CoRR (2020)
Konrad Zolna, Scott E. Reed, Alexander Novikov, Sergio Gómez Colmenarejo, David Budden, Serkan Cabi, Misha Denil, Nando de Freitas, Ziyu Wang
Task-Relevant Adversarial Imitation Learning. CoRL (2020)
Matt Hoffman, Bobak Shahriari, John Aslanides, Gabriel Barth-Maron, Feryal Behbahani, Tamara Norman, Abbas Abdolmaleki, Albin Cassirer, Fan Yang, Kate Baumli, Sarah Henderson, Alexander Novikov, Sergio Gómez Colmenarejo, Serkan Cabi, Çaglar Gülçehre, Tom Le Paine, Andrew Cowie, Ziyu Wang, Bilal Piot, Nando de Freitas
Acme: A Research Framework for Distributed Reinforcement Learning. CoRR (2020)
Ksenia Konyushkova, Konrad Zolna, Yusuf Aytar, Alexander Novikov, Scott E. Reed, Serkan Cabi, Nando de Freitas
Semi-supervised reward learning for offline reinforcement learning. CoRR (2020)
Thomas Pierrot, Guillaume Ligner, Scott E. Reed, Olivier Sigaud, Nicolas Perrin, Alexandre Laterre, David Kas, Karim Beguir, Nando de Freitas
Learning Compositional Neural Programs with Recursive Tree Search and Planning. CoRR (2019)
Natasha Jaques, Angeliki Lazaridou, Edward Hughes, Çaglar Gülçehre, Pedro A. Ortega, DJ Strouse, Joel Z. Leibo, Nando de Freitas
Social Influence as Intrinsic Motivation for Multi-Agent Deep Reinforcement Learning. ICML (2019)
Serkan Cabi, Sergio Gómez Colmenarejo, Alexander Novikov, Ksenia Konyushkova, Scott E. Reed, Rae Jeong, Konrad Zolna, Yusuf Aytar, David Budden, Mel Vecerík, Oleg Sushkov, David Barker, Jonathan Scholz, Misha Denil, Nando de Freitas, Ziyu Wang
A Framework for Data-Driven Robotics. CoRR (2019)
Yutian Chen, Abram L. Friesen, Feryal Behbahani, David Budden, Matthew W. Hoffman, Arnaud Doucet, Nando de Freitas
Modular Meta-Learning with Shrinkage. CoRR (2019)
Thomas Pierrot, Guillaume Ligner, Scott E. Reed, Olivier Sigaud, Nicolas Perrin, Alexandre Laterre, David Kas, Karim Beguir, Nando de Freitas
Learning Compositional Neural Programs with Recursive Tree Search and Planning. NeurIPS (2019)
Brendan Shillingford, Yannis M. Assael, Matthew W. Hoffman, Thomas Paine, Cían Hughes, Utsav Prabhu, Hank Liao, Hasim Sak, Kanishka Rao, Lorrayne Bennett, Marie Mulville, Misha Denil, Ben Coppin, Ben Laurie, Andrew W. Senior, Nando de Freitas
Large-Scale Visual Speech Recognition. INTERSPEECH (2019)
Tom Le Paine, Çaglar Gülçehre, Bobak Shahriari, Misha Denil, Matt Hoffman, Hubert Soyer, Richard Tanburn, Steven Kapturowski, Neil C. Rabinowitz, Duncan Williams, Gabriel Barth-Maron, Ziyu Wang, Nando de Freitas, Worlds Team
Making Efficient Use of Demonstrations to Solve Hard Exploration Problems. CoRR (2019)
Yutian Chen, Yannis M. Assael, Brendan Shillingford, David Budden, Scott E. Reed, Heiga Zen, Quan Wang, Luis C. Cobo, Andrew Trask, Ben Laurie, Çaglar Gülçehre, Aäron van den Oord, Oriol Vinyals, Nando de Freitas
Sample Efficient Adaptive Text-to-Speech. ICLR (Poster) (2019)
Pedro A. Ortega, Jane X. Wang, Mark Rowland, Tim Genewein, Zeb Kurth-Nelson, Razvan Pascanu, Nicolas Heess, Joel Veness, Alexander Pritzel, Pablo Sprechmann, Siddhant M. Jayakumar, Tom McGrath, Kevin J. Miller, Mohammad Gheshlaghi Azar, Ian Osband, Neil C. Rabinowitz, András György, Silvia Chiappa, Simon Osindero, Yee Whye Teh, Hado van Hasselt, Nando de Freitas, Matthew Botvinick, Shane Legg
Meta-learning of Sequential Strategies. CoRR (2019)
Konrad Zolna, Scott E. Reed, Alexander Novikov, Sergio Gomez Colmenarejo, David Budden, Serkan Cabi, Misha Denil, Nando de Freitas, Ziyu Wang
Task-Relevant Adversarial Imitation Learning. CoRR (2019)
Çaglar Gülçehre, Misha Denil, Mateusz Malinowski, Ali Razavi, Razvan Pascanu, Karl Moritz Hermann, Peter W. Battaglia, Victor Bapst, David Raposo, Adam Santoro, Nando de Freitas
Hyperbolic Attention Networks. ICLR (Poster) (2019)
Scott E. Reed, Yutian Chen, Thomas Paine, Aäron van den Oord, S. M. Ali Eslami, Danilo J. Rezende, Oriol Vinyals, Nando de Freitas
Few-shot Autoregressive Density Estimation: Towards Learning to Learn Distributions. ICLR (Poster) (2018)
Edward Choi, Angeliki Lazaridou, Nando de Freitas
Compositional Obverter Communication Learning from Raw Visual Input. ICLR (Poster) (2018)
Yusuf Aytar, Tobias Pfaff, David Budden, Tom Le Paine, Ziyu Wang, Nando de Freitas
Playing hard exploration games by watching YouTube. CoRR (2018)
Yuke Zhu, Ziyu Wang, Josh Merel, Andrei A. Rusu, Tom Erez, Serkan Cabi, Saran Tunyasuvunakool, János Kramár, Raia Hadsell, Nando de Freitas, Nicolas Heess
Reinforcement and Imitation Learning for Diverse Visuomotor Skills. Robotics: Science and Systems (2018)
Edward Choi, Angeliki Lazaridou, Nando de Freitas
Compositional Obverter Communication Learning From Raw Visual Input. CoRR (2018)
Yuke Zhu, Ziyu Wang, Josh Merel, Andrei A. Rusu, Tom Erez, Serkan Cabi, Saran Tunyasuvunakool, János Kramár, Raia Hadsell, Nando de Freitas, Nicolas Heess
Reinforcement and Imitation Learning for Diverse Visuomotor Skills. CoRR (2018)
Yusuf Aytar, Tobias Pfaff, David Budden, Tom Le Paine, Ziyu Wang, Nando de Freitas
Playing hard exploration games by watching YouTube. NeurIPS (2018)
Yutian Chen, Yannis M. Assael, Brendan Shillingford, David Budden, Scott E. Reed, Heiga Zen, Quan Wang, Luis C. Cobo, Andrew Trask, Ben Laurie, Çaglar Gülçehre, Aäron van den Oord, Oriol Vinyals, Nando de Freitas
Sample Efficient Adaptive Text-to-Speech. CoRR (2018)
Yutian Chen, Aja Huang, Ziyu Wang, Ioannis Antonoglou, Julian Schrittwieser, David Silver, Nando de Freitas
Bayesian Optimization in AlphaGo. CoRR (2018)
Tom Le Paine, Sergio Gomez Colmenarejo, Ziyu Wang, Scott E. Reed, Yusuf Aytar, Tobias Pfaff, Matthew W. Hoffman, Gabriel Barth-Maron, Serkan Cabi, David Budden, Nando de Freitas
One-Shot High-Fidelity Imitation: Training Large-Scale Deep Nets with RL. CoRR (2018)
Çaglar Gülçehre, Misha Denil, Mateusz Malinowski, Ali Razavi, Razvan Pascanu, Karl Moritz Hermann, Peter W. Battaglia, Victor Bapst, David Raposo, Adam Santoro, Nando de Freitas
Hyperbolic Attention Networks. CoRR (2018)
Brendan Shillingford, Yannis M. Assael, Matthew W. Hoffman, Thomas Paine, Cían Hughes, Utsav Prabhu, Hank Liao, Hasim Sak, Kanishka Rao, Lorrayne Bennett, Marie Mulville, Ben Coppin, Ben Laurie, Andrew W. Senior, Nando de Freitas
Large-Scale Visual Speech Recognition. CoRR (2018)
Natasha Jaques, Angeliki Lazaridou, Edward Hughes, Çaglar Gülçehre, Pedro A. Ortega, DJ Strouse, Joel Z. Leibo, Nando de Freitas
Intrinsic Social Motivation via Causal Influence in Multi-Agent RL. CoRR (2018)
Brandon Amos, Laurent Dinh, Serkan Cabi, Thomas Rothörl, Sergio Gomez Colmenarejo, Alistair Muldal, Tom Erez, Yuval Tassa, Nando de Freitas, Misha Denil
Learning Awareness Models. ICLR (Poster) (2018)
Brandon Amos, Laurent Dinh, Serkan Cabi, Thomas Rothörl, Sergio Gomez Colmenarejo, Alistair Muldal, Tom Erez, Yuval Tassa, Nando de Freitas, Misha Denil
Learning Awareness Models. CoRR (2018)
Olga Wichrowska, Niru Maheswaranathan, Matthew W. Hoffman, Sergio Gomez Colmenarejo, Misha Denil, Nando de Freitas, Jascha Sohl-Dickstein
Learned Optimizers that Scale and Generalize. ICML (2017)
Ziyu Wang, Josh Merel, Scott E. Reed, Greg Wayne, Nando de Freitas, Nicolas Heess
Robust Imitation of Diverse Behaviors. CoRR (2017)
Yutian Chen, Matthew W. Hoffman, Sergio Gomez Colmenarejo, Misha Denil, Timothy P. Lillicrap, Matthew Botvinick, Nando de Freitas
Learning to Learn without Gradient Descent by Gradient Descent. ICML (2017)
Serkan Cabi, Sergio Gomez Colmenarejo, Matthew W. Hoffman, Misha Denil, Ziyu Wang, Nando de Freitas
The Intentional Unintentional Agent: Learning to Solve Many Continuous Control Tasks Simultaneously. CoRL (2017)
Ziyu Wang, Josh Merel, Scott E. Reed, Nando de Freitas, Gregory Wayne, Nicolas Heess
Robust Imitation of Diverse Behaviors. NIPS (2017)
Scott E. Reed, Aäron van den Oord, Nal Kalchbrenner, Sergio Gomez Colmenarejo, Ziyu Wang, Yutian Chen, Dan Belov, Nando de Freitas
Parallel Multiscale Autoregressive Density Estimation. ICML (2017)
Misha Denil, Pulkit Agrawal, Tejas D. Kulkarni, Tom Erez, Peter W. Battaglia, Nando de Freitas
Learning to Perform Physics Experiments via Deep Reinforcement Learning. ICLR (Poster) (2017)
Rui Ponte Costa, Yannis M. Assael, Brendan Shillingford, Nando de Freitas, Tim P. Vogels
Cortical microcircuits as gated-recurrent neural networks. CoRR (2017)
Misha Denil, Sergio Gomez Colmenarejo, Serkan Cabi, David Saxton, Nando de Freitas
Programmable Agents. CoRR (2017)
Ziyu Wang, Victor Bapst, Nicolas Heess, Volodymyr Mnih, Rémi Munos, Koray Kavukcuoglu, Nando de Freitas
Sample Efficient Actor-Critic with Experience Replay. ICLR (Poster) (2017)
Scott E. Reed, Aäron van den Oord, Nal Kalchbrenner, Sergio Gomez Colmenarejo, Ziyu Wang, Dan Belov, Nando de Freitas
Parallel Multiscale Autoregressive Density Estimation. CoRR (2017)
Scott E. Reed, Yutian Chen, Thomas Paine, Aäron van den Oord, S. M. Ali Eslami, Danilo Jimenez Rezende, Oriol Vinyals, Nando de Freitas
Few-shot Autoregressive Density Estimation: Towards Learning to Learn Distributions. CoRR (2017)
Matthew Botvinick, David G. T. Barrett, Peter W. Battaglia, Nando de Freitas, Dharshan Kumaran, Joel Z. Leibo, Tim Lillicrap, Joseph Modayil, S. Mohamed, Neil C. Rabinowitz, Danilo Jimenez Rezende, Adam Santoro, Tom Schaul, Christopher Summerfield, Greg Wayne, Theophane Weber, Daan Wierstra, Shane Legg, Demis Hassabis
Building Machines that Learn and Think for Themselves: Commentary on Lake et al., Behavioral and Brain Sciences, 2017. CoRR (2017)
Serkan Cabi, Sergio Gomez Colmenarejo, Matthew W. Hoffman, Misha Denil, Ziyu Wang, Nando de Freitas
The Intentional Unintentional Agent: Learning to Solve Many Continuous Control Tasks Simultaneously. CoRR (2017)
Olga Wichrowska, Niru Maheswaranathan, Matthew W. Hoffman, Sergio Gomez Colmenarejo, Misha Denil, Nando de Freitas, Jascha Sohl-Dickstein
Learned Optimizers that Scale and Generalize. CoRR (2017)
Rui Ponte Costa, Yannis M. Assael, Brendan Shillingford, Nando de Freitas, Tim P. Vogels
Cortical microcircuits as gated-recurrent neural networks. NIPS (2017)
Bobak Shahriari, Alexandre Bouchard-Côté, Nando de Freitas
Unbounded Bayesian Optimization via Regularization. AISTATS (2016)
Jakob N. Foerster, Yannis M. Assael, Nando de Freitas, Shimon Whiteson
Learning to Communicate with Deep Multi-Agent Reinforcement Learning. NIPS (2016)
Jakob N. Foerster, Yannis M. Assael, Nando de Freitas, Shimon Whiteson
Learning to Communicate with Deep Multi-Agent Reinforcement Learning. CoRR (2016)
Ziyu Wang, Tom Schaul, Matteo Hessel, Hado van Hasselt, Marc Lanctot, Nando de Freitas
Dueling Network Architectures for Deep Reinforcement Learning. ICML (2016)
Marcin Andrychowicz, Misha Denil, Sergio Gomez Colmenarejo, Matthew W. Hoffman, David Pfau, Tom Schaul, Nando de Freitas
Learning to learn by gradient descent by gradient descent. CoRR (2016)
Yutian Chen, Luke Bornn, Nando de Freitas, Mareija Eskelin, Jing Fang, Max Welling
Herded Gibbs Sampling. J. Mach. Learn. Res. 17 (2016)
Bobak Shahriari, Kevin Swersky, Ziyu Wang, Ryan P. Adams, Nando de Freitas
Taking the Human Out of the Loop: A Review of Bayesian Optimization. Proc. IEEE 104 (1) (2016)
Scott E. Reed, Nando de Freitas
Neural Programmer-Interpreters. ICLR (2016)
Misha Denil, Pulkit Agrawal, Tejas D. Kulkarni, Tom Erez, Peter W. Battaglia, Nando de Freitas
Learning to Perform Physics Experiments via Deep Reinforcement Learning. CoRR (2016)
Ziyu Wang, Victor Bapst, Nicolas Heess, Volodymyr Mnih, Rémi Munos, Koray Kavukcuoglu, Nando de Freitas
Sample Efficient Actor-Critic with Experience Replay. CoRR (2016)
Jakob N. Foerster, Yannis M. Assael, Nando de Freitas, Shimon Whiteson
Learning to Communicate to Solve Riddles with Deep Distributed Recurrent Q-Networks. CoRR (2016)
Nando de Freitas
Learning to Learn and Compositionality with Deep Recurrent Neural Networks: Learning to Learn and Compositionality. KDD (2016)
Marcin Moczulski, Misha Denil, Jeremy Appleyard, Nando de Freitas
ACDC: A Structured Efficient Linear Layer. ICLR (Poster) (2016)
Yutian Chen, Matthew W. Hoffman, Sergio Gomez Colmenarejo, Misha Denil, Timothy P. Lillicrap, Nando de Freitas
Learning to Learn for Global Optimization of Black Box Functions. CoRR (2016)
Yannis M. Assael, Brendan Shillingford, Shimon Whiteson, Nando de Freitas
LipNet: Sentence-level Lipreading. CoRR (2016)
Ziyu Wang, Frank Hutter, Masrour Zoghi, David Matheson, Nando de Freitas
Bayesian Optimization in a Billion Dimensions via Random Embeddings. J. Artif. Intell. Res. 55 (2016)
Marcin Andrychowicz, Misha Denil, Sergio Gomez Colmenarejo, Matthew W. Hoffman, David Pfau, Tom Schaul, Nando de Freitas
Learning to learn by gradient descent by gradient descent. NIPS (2016)
Aurore Lyon, Ana Mincholé, Rina Ariga, Pablo Laguna, Stefan Neubauer, Hugh Watkins, Nando de Freitas, Blanca Rodríguez
Extraction of Morphological QRS-based Biomarkers in Hypertrophic Cardiomyopathy for Risk Stratification Using L1 Regularized Logistic Regression. CinC (2015)
Zichao Yang, Marcin Moczulski, Misha Denil, Nando de Freitas, Alexander J. Smola, Le Song, Ziyu Wang
Deep Fried Convnets. ICCV (2015)
Dimitrios Kotzias, Misha Denil, Nando de Freitas, Padhraic Smyth
From Group to Individual Labels Using Deep Features. KDD (2015)
Miroslav Bogdanovic, Dejan Markovikj, Misha Denil, Nando de Freitas
Deep Apprenticeship Learning for Playing Video Games. AAAI Workshop: Learning for General Competency in Video Games (2015)

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Publication Activity (10 Years)

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