Nando de Freitas

210 papers A* 32A 26B 1C 1Misc 5Journal 103Unranked 39

Year	Rank	Type	Title / Venue / Authors
2024	A*	`conf`	Genie: Generative Interactive Environments. ICML 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 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
2024	J	`jnl`	Genie: Generative Interactive Environments. CoRR 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 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
2024	J	`jnl`	Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models. CoRR 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
2023	J	`jnl`	AlphaStar Unplugged: Large-Scale Offline Reinforcement Learning. CoRR 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
2023	J	`jnl`	Knowledge Transfer from Teachers to Learners in Growing-Batch Reinforcement Learning. CoRR Patrick Emedom-Nnamdi, Abram L. Friesen, Bobak Shahriari, Nando de Freitas, Matthew W. Hoffman
2023	J	`jnl`	Machine Learning for Ancient Languages: A Survey. Comput. Linguistics Thea Sommerschield, Yannis M. Assael, John Pavlopoulos, Vanessa Stefanak, Andrew W. Senior, Chris Dyer, John Bodel, Jonathan Prag, Ion Androutsopoulos, Nando de Freitas
2023	J	`jnl`	Reinforced Self-Training (ReST) for Language Modeling. CoRR 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
2023	—	`conf`	Vision-Language Models as Success Detectors. CoLLAs Yuqing Du, Ksenia Konyushkova, Misha Denil, Akhil Raju, Jessica Landon, Felix Hill, Nando de Freitas, Serkan Cabi
2023	J	`jnl`	Vision-Language Models as Success Detectors. CoRR Yuqing Du, Ksenia Konyushkova, Misha Denil, Akhil Raju, Jessica Landon, Felix Hill, Nando de Freitas, Serkan Cabi
2022	J	`jnl`	A Generalist Agent. CoRR 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
2022	J	`jnl`	A Generalist Agent. Trans. Mach. Learn. Res. 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
2022	J	`jnl`	Competition-Level Code Generation with AlphaCode. CoRR 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
2022	J	`jnl`	Multi-step Planning for Automated Hyperparameter Optimization with OptFormer. CoRR Lucio M. Dery, Abram L. Friesen, Nando de Freitas, Marc'Aurelio Ranzato, Yutian Chen
2022	J	`jnl`	On Instrumental Variable Regression for Deep Offline Policy Evaluation. J. Mach. Learn. Res. Yutian Chen, Liyuan Xu, Çaglar Gülçehre, Tom Le Paine, Arthur Gretton, Nando de Freitas, Arnaud Doucet
2022	J	`jnl`	Restoring and attributing ancient texts using deep neural networks. Nat. Yannis M. Assael, Thea Sommerschield, Brendan Shillingford, Mahyar Bordbar, John Pavlopoulos, Marita Chatzipanagiotou, Ion Androutsopoulos, Jonathan Prag, Nando de Freitas
2022	A*	`conf`	Towards Learning Universal Hyperparameter Optimizers with Transformers. NeurIPS 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
2022	J	`jnl`	Towards Learning Universal Hyperparameter Optimizers with Transformers. CoRR 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
2021	A*	`conf`	Active Offline Policy Selection. NeurIPS Ksenia Konyushkova, Yutian Chen, Thomas Paine, Çaglar Gülçehre, Cosmin Paduraru, Daniel J. Mankowitz, Misha Denil, Nando de Freitas
2021	J	`jnl`	Active Offline Policy Selection. CoRR Ksenia Konyushkova, Yutian Chen, Thomas Paine, Çaglar Gülçehre, Cosmin Paduraru, Daniel J. Mankowitz, Misha Denil, Nando de Freitas
2021	A*	`conf`	Learning Deep Features in Instrumental Variable Regression. ICLR Liyuan Xu, Yutian Chen, Siddarth Srinivasan, Nando de Freitas, Arnaud Doucet, Arthur Gretton
2021	J	`jnl`	On Instrumental Variable Regression for Deep Offline Policy Evaluation. CoRR Yutian Chen, Liyuan Xu, Çaglar Gülçehre, Tom Le Paine, Arthur Gretton, Nando de Freitas, Arnaud Doucet
2021	J	`jnl`	Regularized Behavior Value Estimation. CoRR Çaglar Gülçehre, Sergio Gómez Colmenarejo, Ziyu Wang, Jakub Sygnowski, Thomas Paine, Konrad Zolna, Yutian Chen, Matthew W. Hoffman, Razvan Pascanu, Nando de Freitas
2021	J	`jnl`	Shaking the foundations: delusions in sequence models for interaction and control. CoRR 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
2020	J	`jnl`	Acme: A Research Framework for Distributed Reinforcement Learning. CoRR Matt Hoffman, Bobak Shahriari, John Aslanides, Gabriel Barth-Maron, Feryal M. P. 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
2020	A*	`conf`	Critic Regularized Regression. NeurIPS 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
2020	J	`jnl`	Critic Regularized Regression. CoRR 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
2020	J	`jnl`	Hyperparameter Selection for Offline Reinforcement Learning. CoRR Tom Le Paine, Cosmin Paduraru, Andrea Michi, Çaglar Gülçehre, Konrad Zolna, Alexander Novikov, Ziyu Wang, Nando de Freitas
2020	J	`jnl`	Large-scale multilingual audio visual dubbing. CoRR 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
2020	J	`jnl`	Learning Compositional Neural Programs for Continuous Control. CoRR Thomas Pierrot, Nicolas Perrin, Feryal M. P. Behbahani, Alexandre Laterre, Olivier Sigaud, Karim Beguir, Nando de Freitas
2020	J	`jnl`	Learning Deep Features in Instrumental Variable Regression. CoRR Liyuan Xu, Yutian Chen, Siddarth Srinivasan, Nando de Freitas, Arnaud Doucet, Arthur Gretton
2020	A*	`conf`	Making Efficient Use of Demonstrations to Solve Hard Exploration Problems. ICLR 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
2020	A*	`conf`	Modular Meta-Learning with Shrinkage. NeurIPS Yutian Chen, Abram L. Friesen, Feryal M. P. Behbahani, Arnaud Doucet, David Budden, Matthew Hoffman, Nando de Freitas
2020	J	`jnl`	Offline Learning from Demonstrations and Unlabeled Experience. CoRR Konrad Zolna, Alexander Novikov, Ksenia Konyushkova, Çaglar Gülçehre, Ziyu Wang, Yusuf Aytar, Misha Denil, Nando de Freitas, Scott E. Reed
2020	A*	`conf`	RL Unplugged: A Collection of Benchmarks for Offline Reinforcement Learning. NeurIPS 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
2020	J	`jnl`	RL Unplugged: Benchmarks for Offline Reinforcement Learning. CoRR 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
2020	—	`conf`	Scaling data-driven robotics with reward sketching and batch reinforcement learning. Robotics: Science and Systems 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
2020	J	`jnl`	Semi-supervised reward learning for offline reinforcement learning. CoRR Ksenia Konyushkova, Konrad Zolna, Yusuf Aytar, Alexander Novikov, Scott E. Reed, Serkan Cabi, Nando de Freitas
2020	Misc	`conf`	Task-Relevant Adversarial Imitation Learning. CoRL Konrad Zolna, Scott E. Reed, Alexander Novikov, Sergio Gómez Colmenarejo, David Budden, Serkan Cabi, Misha Denil, Nando de Freitas, Ziyu Wang
2019	J	`jnl`	A Framework for Data-Driven Robotics. CoRR 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
2019	—	`conf`	Hyperbolic Attention Networks. ICLR (Poster) 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
2019	A	`conf`	Large-Scale Visual Speech Recognition. INTERSPEECH 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
2019	A*	`conf`	Learning Compositional Neural Programs with Recursive Tree Search and Planning. NeurIPS Thomas Pierrot, Guillaume Ligner, Scott E. Reed, Olivier Sigaud, Nicolas Perrin, Alexandre Laterre, David Kas, Karim Beguir, Nando de Freitas
2019	J	`jnl`	Learning Compositional Neural Programs with Recursive Tree Search and Planning. CoRR Thomas Pierrot, Guillaume Ligner, Scott E. Reed, Olivier Sigaud, Nicolas Perrin, Alexandre Laterre, David Kas, Karim Beguir, Nando de Freitas
2019	J	`jnl`	Making Efficient Use of Demonstrations to Solve Hard Exploration Problems. CoRR 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
2019	J	`jnl`	Meta-learning of Sequential Strategies. CoRR 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 M. Botvinick, Shane Legg
2019	J	`jnl`	Modular Meta-Learning with Shrinkage. CoRR Yutian Chen, Abram L. Friesen, Feryal M. P. Behbahani, David Budden, Matthew W. Hoffman, Arnaud Doucet, Nando de Freitas
2019	—	`conf`	Sample Efficient Adaptive Text-to-Speech. ICLR (Poster) 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
2019	A*	`conf`	Social Influence as Intrinsic Motivation for Multi-Agent Deep Reinforcement Learning. ICML Natasha Jaques, Angeliki Lazaridou, Edward Hughes, Çaglar Gülçehre, Pedro A. Ortega, DJ Strouse, Joel Z. Leibo, Nando de Freitas
2019	J	`jnl`	Task-Relevant Adversarial Imitation Learning. CoRR Konrad Zolna, Scott E. Reed, Alexander Novikov, Sergio Gomez Colmenarejo, David Budden, Serkan Cabi, Misha Denil, Nando de Freitas, Ziyu Wang
2018	J	`jnl`	Bayesian Optimization in AlphaGo. CoRR Yutian Chen, Aja Huang, Ziyu Wang, Ioannis Antonoglou, Julian Schrittwieser, David Silver, Nando de Freitas
2018	J	`jnl`	Compositional Obverter Communication Learning From Raw Visual Input. CoRR Edward Choi, Angeliki Lazaridou, Nando de Freitas
2018	—	`conf`	Compositional Obverter Communication Learning from Raw Visual Input. ICLR (Poster) Edward Choi, Angeliki Lazaridou, Nando de Freitas
2018	—	`conf`	Few-shot Autoregressive Density Estimation: Towards Learning to Learn Distributions. ICLR (Poster) Scott E. Reed, Yutian Chen, Thomas Paine, Aäron van den Oord, S. M. Ali Eslami, Danilo J. Rezende, Oriol Vinyals, Nando de Freitas
2018	J	`jnl`	Hyperbolic Attention Networks. CoRR 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
2018	J	`jnl`	Intrinsic Social Motivation via Causal Influence in Multi-Agent RL. CoRR Natasha Jaques, Angeliki Lazaridou, Edward Hughes, Çaglar Gülçehre, Pedro A. Ortega, DJ Strouse, Joel Z. Leibo, Nando de Freitas
2018	J	`jnl`	Large-Scale Visual Speech Recognition. CoRR 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
2018	—	`conf`	Learning Awareness Models. ICLR (Poster) Brandon Amos, Laurent Dinh, Serkan Cabi, Thomas Rothörl, Sergio Gomez Colmenarejo, Alistair Muldal, Tom Erez, Yuval Tassa, Nando de Freitas, Misha Denil
2018	J	`jnl`	Learning Awareness Models. CoRR Brandon Amos, Laurent Dinh, Serkan Cabi, Thomas Rothörl, Sergio Gomez Colmenarejo, Alistair Muldal, Tom Erez, Yuval Tassa, Nando de Freitas, Misha Denil
2018	J	`jnl`	One-Shot High-Fidelity Imitation: Training Large-Scale Deep Nets with RL. CoRR 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
2018	A*	`conf`	Playing hard exploration games by watching YouTube. NeurIPS Yusuf Aytar, Tobias Pfaff, David Budden, Tom Le Paine, Ziyu Wang, Nando de Freitas
2018	J	`jnl`	Playing hard exploration games by watching YouTube. CoRR Yusuf Aytar, Tobias Pfaff, David Budden, Tom Le Paine, Ziyu Wang, Nando de Freitas
2018	—	`conf`	Reinforcement and Imitation Learning for Diverse Visuomotor Skills. Robotics: Science and Systems Yuke Zhu, Ziyu Wang, Josh Merel, Andrei A. Rusu, Tom Erez, Serkan Cabi, Saran Tunyasuvunakool, János Kramár, Raia Hadsell, Nando de Freitas, Nicolas Heess
2018	J	`jnl`	Reinforcement and Imitation Learning for Diverse Visuomotor Skills. CoRR Yuke Zhu, Ziyu Wang, Josh Merel, Andrei A. Rusu, Tom Erez, Serkan Cabi, Saran Tunyasuvunakool, János Kramár, Raia Hadsell, Nando de Freitas, Nicolas Heess
2018	J	`jnl`	Sample Efficient Adaptive Text-to-Speech. CoRR 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
2017	J	`jnl`	Building Machines that Learn and Think for Themselves: Commentary on Lake et al., Behavioral and Brain Sciences, 2017. CoRR Matthew M. 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
2017	—	`conf`	Cortical microcircuits as gated-recurrent neural networks. NIPS Rui Ponte Costa, Yannis M. Assael, Brendan Shillingford, Nando de Freitas, Tim P. Vogels
2017	J	`jnl`	Cortical microcircuits as gated-recurrent neural networks. CoRR Rui Ponte Costa, Yannis M. Assael, Brendan Shillingford, Nando de Freitas, Tim P. Vogels
2017	J	`jnl`	Few-shot Autoregressive Density Estimation: Towards Learning to Learn Distributions. CoRR Scott E. Reed, Yutian Chen, Thomas Paine, Aäron van den Oord, S. M. Ali Eslami, Danilo Jimenez Rezende, Oriol Vinyals, Nando de Freitas
2017	A*	`conf`	Learned Optimizers that Scale and Generalize. ICML Olga Wichrowska, Niru Maheswaranathan, Matthew W. Hoffman, Sergio Gomez Colmenarejo, Misha Denil, Nando de Freitas, Jascha Sohl-Dickstein
2017	J	`jnl`	Learned Optimizers that Scale and Generalize. CoRR Olga Wichrowska, Niru Maheswaranathan, Matthew W. Hoffman, Sergio Gomez Colmenarejo, Misha Denil, Nando de Freitas, Jascha Sohl-Dickstein
2017	A*	`conf`	Learning to Learn without Gradient Descent by Gradient Descent. ICML Yutian Chen, Matthew W. Hoffman, Sergio Gomez Colmenarejo, Misha Denil, Timothy P. Lillicrap, Matthew M. Botvinick, Nando de Freitas
2017	—	`conf`	Learning to Perform Physics Experiments via Deep Reinforcement Learning. ICLR (Poster) Misha Denil, Pulkit Agrawal, Tejas D. Kulkarni, Tom Erez, Peter W. Battaglia, Nando de Freitas
2017	A*	`conf`	Parallel Multiscale Autoregressive Density Estimation. ICML Scott E. Reed, Aäron van den Oord, Nal Kalchbrenner, Sergio Gomez Colmenarejo, Ziyu Wang, Yutian Chen, Dan Belov, Nando de Freitas
2017	J	`jnl`	Parallel Multiscale Autoregressive Density Estimation. CoRR Scott E. Reed, Aäron van den Oord, Nal Kalchbrenner, Sergio Gomez Colmenarejo, Ziyu Wang, Dan Belov, Nando de Freitas
2017	J	`jnl`	Programmable Agents. CoRR Misha Denil, Sergio Gomez Colmenarejo, Serkan Cabi, David Saxton, Nando de Freitas
2017	—	`conf`	Robust Imitation of Diverse Behaviors. NIPS Ziyu Wang, Josh Merel, Scott E. Reed, Nando de Freitas, Gregory Wayne, Nicolas Heess
2017	J	`jnl`	Robust Imitation of Diverse Behaviors. CoRR Ziyu Wang, Josh Merel, Scott E. Reed, Greg Wayne, Nando de Freitas, Nicolas Heess
2017	—	`conf`	Sample Efficient Actor-Critic with Experience Replay. ICLR (Poster) Ziyu Wang, Victor Bapst, Nicolas Heess, Volodymyr Mnih, Rémi Munos, Koray Kavukcuoglu, Nando de Freitas
2017	Misc	`conf`	The Intentional Unintentional Agent: Learning to Solve Many Continuous Control Tasks Simultaneously. CoRL Serkan Cabi, Sergio Gomez Colmenarejo, Matthew W. Hoffman, Misha Denil, Ziyu Wang, Nando de Freitas
2017	J	`jnl`	The Intentional Unintentional Agent: Learning to Solve Many Continuous Control Tasks Simultaneously. CoRR Serkan Cabi, Sergio Gomez Colmenarejo, Matthew W. Hoffman, Misha Denil, Ziyu Wang, Nando de Freitas
2016	A*	`conf`	ACDC: A Structured Efficient Linear Layer. ICLR (Poster) Marcin Moczulski, Misha Denil, Jeremy Appleyard, Nando de Freitas
2016	J	`jnl`	Bayesian Optimization in a Billion Dimensions via Random Embeddings. J. Artif. Intell. Res. Ziyu Wang, Frank Hutter, Masrour Zoghi, David Matheson, Nando de Freitas
2016	A*	`conf`	Dueling Network Architectures for Deep Reinforcement Learning. ICML Ziyu Wang, Tom Schaul, Matteo Hessel, Hado van Hasselt, Marc Lanctot, Nando de Freitas
2016	J	`jnl`	Herded Gibbs Sampling. J. Mach. Learn. Res. Yutian Chen, Luke Bornn, Nando de Freitas, Mareija Eskelin, Jing Fang, Max Welling
2016	J	`jnl`	Learning to Communicate to Solve Riddles with Deep Distributed Recurrent Q-Networks. CoRR Jakob N. Foerster, Yannis M. Assael, Nando de Freitas, Shimon Whiteson
2016	—	`conf`	Learning to Communicate with Deep Multi-Agent Reinforcement Learning. NIPS Jakob N. Foerster, Yannis M. Assael, Nando de Freitas, Shimon Whiteson
2016	J	`jnl`	Learning to Communicate with Deep Multi-Agent Reinforcement Learning. CoRR Jakob N. Foerster, Yannis M. Assael, Nando de Freitas, Shimon Whiteson
2016	A*	`conf`	Learning to Learn and Compositionality with Deep Recurrent Neural Networks: Learning to Learn and Compositionality. KDD Nando de Freitas
2016	J	`jnl`	Learning to Learn for Global Optimization of Black Box Functions. CoRR Yutian Chen, Matthew W. Hoffman, Sergio Gomez Colmenarejo, Misha Denil, Timothy P. Lillicrap, Nando de Freitas
2016	J	`jnl`	Learning to Perform Physics Experiments via Deep Reinforcement Learning. CoRR Misha Denil, Pulkit Agrawal, Tejas D. Kulkarni, Tom Erez, Peter W. Battaglia, Nando de Freitas
2016	—	`conf`	Learning to learn by gradient descent by gradient descent. NIPS Marcin Andrychowicz, Misha Denil, Sergio Gomez Colmenarejo, Matthew W. Hoffman, David Pfau, Tom Schaul, Nando de Freitas
2016	J	`jnl`	Learning to learn by gradient descent by gradient descent. CoRR Marcin Andrychowicz, Misha Denil, Sergio Gomez Colmenarejo, Matthew W. Hoffman, David Pfau, Tom Schaul, Nando de Freitas
2016	J	`jnl`	LipNet: Sentence-level Lipreading. CoRR Yannis M. Assael, Brendan Shillingford, Shimon Whiteson, Nando de Freitas
2016	A*	`conf`	Neural Programmer-Interpreters. ICLR Scott E. Reed, Nando de Freitas
2016	J	`jnl`	Sample Efficient Actor-Critic with Experience Replay. CoRR Ziyu Wang, Victor Bapst, Nicolas Heess, Volodymyr Mnih, Rémi Munos, Koray Kavukcuoglu, Nando de Freitas
2016	J	`jnl`	Taking the Human Out of the Loop: A Review of Bayesian Optimization. Proc. IEEE Bobak Shahriari, Kevin Swersky, Ziyu Wang, Ryan P. Adams, Nando de Freitas
2016	A	`conf`	Unbounded Bayesian Optimization via Regularization. AISTATS Bobak Shahriari, Alexandre Bouchard-Côté, Nando de Freitas
2015	—	`conf`	Deep Apprenticeship Learning for Playing Video Games. AAAI Workshop: Learning for General Competency in Video Games Miroslav Bogdanovic, Dejan Markovikj, Misha Denil, Nando de Freitas
2015	A*	`conf`	Deep Fried Convnets. ICCV Zichao Yang, Marcin Moczulski, Misha Denil, Nando de Freitas, Alexander J. Smola, Le Song, Ziyu Wang
2015	J	`jnl`	Dueling Network Architectures for Deep Reinforcement Learning. CoRR Ziyu Wang, Nando de Freitas, Marc Lanctot
2015	—	`conf`	Extraction of Morphological QRS-based Biomarkers in Hypertrophic Cardiomyopathy for Risk Stratification Using L1 Regularized Logistic Regression. CinC Aurore Lyon, Ana Mincholé, Rina Ariga, Pablo Laguna, Stefan Neubauer, Hugh Watkins, Nando de Freitas, Blanca Rodríguez
2015	A*	`conf`	From Group to Individual Labels Using Deep Features. KDD Dimitrios Kotzias, Misha Denil, Nando de Freitas, Padhraic Smyth
2014	J	`jnl`	A Deep Architecture for Semantic Parsing. CoRR Edward Grefenstette, Phil Blunsom, Nando de Freitas, Karl Moritz Hermann
2014	J	`jnl`	An Entropy Search Portfolio for Bayesian Optimization. CoRR Bobak Shahriari, Ziyu Wang, Matthew W. Hoffman, Alexandre Bouchard-Côté, Nando de Freitas
2014	A	`conf`	Bayesian Multi-Scale Optimistic Optimization. AISTATS Ziyu Wang, Babak Shakibi, Lin Jin, Nando de Freitas
2014	J	`jnl`	Bayesian Multi-Scale Optimistic Optimization. CoRR Ziyu Wang, Babak Shakibi, Lin Jin, Nando de Freitas
2014	A	`conf`	Bayesian Optimization with an Empirical Hardness Model for approximate Nearest Neighbour Search. WACV Julieta Martinez, James J. Little, Nando de Freitas
2014	J	`jnl`	Deep Fried Convnets. CoRR Zichao Yang, Marcin Moczulski, Misha Denil, Nando de Freitas, Alexander J. Smola, Le Song, Ziyu Wang
2014	J	`jnl`	Deep Multi-Instance Transfer Learning. CoRR Dimitrios Kotzias, Misha Denil, Phil Blunsom, Nando de Freitas
2014	—	`conf`	Distributed Parameter Estimation in Probabilistic Graphical Models. NIPS Yariv Dror Mizrahi, Misha Denil, Nando de Freitas
2014	J	`jnl`	Extraction of Salient Sentences from Labelled Documents. CoRR Misha Denil, Alban Demiraj, Nando de Freitas
2014	J	`jnl`	Heteroscedastic Treed Bayesian Optimisation. CoRR John-Alexander M. Assael, Ziyu Wang, Nando de Freitas
2014	A*	`conf`	Linear and Parallel Learning of Markov Random Fields. ICML Yariv Dror Mizrahi, Misha Denil, Nando de Freitas
2014	J	`jnl`	Modelling, Visualising and Summarising Documents with a Single Convolutional Neural Network. CoRR Misha Denil, Alban Demiraj, Nal Kalchbrenner, Phil Blunsom, Nando de Freitas
2014	A*	`conf`	Narrowing the Gap: Random Forests In Theory and In Practice. ICML Misha Denil, David Matheson, Nando de Freitas
2014	A	`conf`	On correlation and budget constraints in model-based bandit optimization with application to automatic machine learning. AISTATS Matthew W. Hoffman, Bobak Shahriari, Nando de Freitas
2014	J	`jnl`	Theoretical Analysis of Bayesian Optimisation with Unknown Gaussian Process Hyper-Parameters. CoRR Ziyu Wang, Nando de Freitas
2013	—	`conf`	Adaptive Hamiltonian and Riemann Manifold Monte Carlo. ICML (3) Ziyu Wang, Shakir Mohamed, Nando de Freitas
2013	A*	`conf`	Bayesian Optimization in High Dimensions via Random Embeddings. IJCAI Ziyu Wang, Masrour Zoghi, Frank Hutter, David Matheson, Nando de Freitas
2013	J	`jnl`	Bayesian Optimization in a Billion Dimensions via Random Embeddings CoRR Ziyu Wang, Masrour Zoghi, Frank Hutter, David Matheson, Nando de Freitas
2013	J	`jnl`	Best arm identification via Bayesian gap-based exploration CoRR Matthew W. Hoffman, Bobak Shahriari, Nando de Freitas
2013	—	`conf`	Consistency of Online Random Forests. ICML (3) Misha Denil, David Matheson, Nando de Freitas
2013	J	`jnl`	Efficient Learning of Practical Markov Random Fields with Exact Inference. CoRR Yariv Dror Mizrahi, Nando de Freitas, Luis Tenorio
2013	A*	`conf`	Herded Gibbs Sampling ICLR Luke Bornn, Yutian Chen, Nando de Freitas, Mareija Eskelin, Jing Fang, Max Welling
2013	J	`jnl`	Narrowing the Gap: Random Forests In Theory and In Practice. CoRR Misha Denil, David Matheson, Nando de Freitas
2013	—	`conf`	Predicting Parameters in Deep Learning. NIPS Misha Denil, Babak Shakibi, Laurent Dinh, Marc'Aurelio Ranzato, Nando de Freitas
2013	J	`jnl`	Predicting Parameters in Deep Learning. CoRR Misha Denil, Babak Shakibi, Laurent Dinh, Marc'Aurelio Ranzato, Nando de Freitas
2013	J	`jnl`	Proceedings of the Twenty-Eighth Conference on Uncertainty in Artificial Intelligence (2012) CoRR Nando de Freitas, Kevin P. Murphy
2013	J	`jnl`	Rao-Blackwellised Particle Filtering for Dynamic Bayesian Networks CoRR Arnaud Doucet, Nando de Freitas, Kevin P. Murphy, Stuart Russell
2013	J	`jnl`	Reversible Jump MCMC Simulated Annealing for Neural Networks CoRR Christophe Andrieu, Nando de Freitas, Arnaud Doucet
2013	J	`jnl`	Self-Avoiding Random Dynamics on Integer Complex Systems. ACM Trans. Model. Comput. Simul. Firas Hamze, Ziyu Wang, Nando de Freitas
2013	J	`jnl`	Variational MCMC CoRR Nando de Freitas, Pedro A. d. F. R. Højen-Sørensen, Michael I. Jordan, Stuart Russell
2012	B	`conf`	A Machine Learning Perspective on Predictive Coding with PAQ8. DCC Byron Knoll, Nando de Freitas
2012	A	`conf`	Adaptive MCMC with Bayesian Optimization. AISTATS Nimalan Mahendran, Ziyu Wang, Firas Hamze, Nando de Freitas
2012	J	`jnl`	Asymptotic Efficiency of Deterministic Estimators for Discrete Energy-Based Models: Ratio Matching and Pseudolikelihood CoRR Benjamin M. Marlin, Nando de Freitas
2012	J	`jnl`	Decentralized, Adaptive, Look-Ahead Particle Filtering CoRR Mohamed Osama Ahmed, Pouyan T. Bibalan, Nando de Freitas, Simon Fauvel
2012	A*	`conf`	Exponential Regret Bounds for Gaussian Process Bandits with Deterministic Observations. ICML Nando de Freitas, Alexander J. Smola, Masrour Zoghi
2012	J	`jnl`	From Fields to Trees CoRR Firas Hamze, Nando de Freitas
2012	J	`jnl`	Intracluster Moves for Constrained Discrete-Space MCMC CoRR Firas Hamze, Nando de Freitas
2012	J	`jnl`	Large-Flip Importance Sampling CoRR Firas Hamze, Nando de Freitas
2012	J	`jnl`	Learning Where to Attend with Deep Architectures for Image Tracking. Neural Comput. Misha Denil, Loris Bazzani, Hugo Larochelle, Nando de Freitas
2012	J	`jnl`	Learning about individuals from group statistics CoRR Hendrik Kück, Nando de Freitas
2012	J	`jnl`	New inference strategies for solving Markov Decision Processes using reversible jump MCMC CoRR Matthias Hoffman, Hendrik Kück, Nando de Freitas, Arnaud Doucet
2012	J	`jnl`	Nonparametric Bayesian Logic CoRR Peter Carbonetto, Jacek Kisynski, Nando de Freitas, David Poole
2012	A	`conf`	On Sparse, Spectral and Other Parameterizations of Binary Probabilistic Models. AISTATS David Buchman, Mark Schmidt, Shakir Mohamed, David Poole, Nando de Freitas
2012	A*	`conf`	Prediction and Fault Detection of Environmental Signals with Uncharacterised Faults. AAAI Michael A. Osborne, Roman Garnett, Kevin Swersky, Nando de Freitas
2012	A	`ed.`	Proceedings of the Twenty-Eighth Conference on Uncertainty in Artificial Intelligence, Catalina Island, CA, USA, August 14-18, 2012 UAI Nando de Freitas, Kevin P. Murphy
2012	J	`jnl`	Recklessly Approximate Sparse Coding CoRR Misha Denil, Nando de Freitas
2012	J	`jnl`	Regret Bounds for Deterministic Gaussian Process Bandits CoRR Nando de Freitas, Alexander J. Smola, Masrour Zoghi
2012	J	`jnl`	Toward Practical N2 Monte Carlo: the Marginal Particle Filter CoRR Mike Klaas, Nando de Freitas, Arnaud Doucet
2011	J	`jnl`	A Machine Learning Perspective on Predictive Coding with PAQ CoRR Byron Knoll, Nando de Freitas
2011	A	`conf`	Asymptotic Efficiency of Deterministic Estimators for Discrete Energy-Based Models: Ratio Matching and Pseudolikelihood. UAI Benjamin M. Marlin, Nando de Freitas
2011	A*	`conf`	Learning attentional policies for tracking and recognition in video with deep networks. ICML Loris Bazzani, Nando de Freitas, Hugo Larochelle, Vittorio Murino, Jo-Anne Ting
2011	J	`jnl`	Learning where to Attend with Deep Architectures for Image Tracking CoRR Misha Denil, Loris Bazzani, Hugo Larochelle, Nando de Freitas
2011	A*	`conf`	On Autoencoders and Score Matching for Energy Based Models. ICML Kevin Swersky, Marc'Aurelio Ranzato, David Buchman, Benjamin M. Marlin, Nando de Freitas
2011	A	`conf`	Portfolio Allocation for Bayesian Optimization. UAI Matthew Hoffman, Eric Brochu, Nando de Freitas
2010	—	`conf`	A Bayesian Interactive Optimization Approach to Procedural Animation Design. Symposium on Computer Animation Eric Brochu, Tyson Brochu, Nando de Freitas
2010	J	`jnl`	A Tutorial on Bayesian Optimization of Expensive Cost Functions, with Application to Active User Modeling and Hierarchical Reinforcement Learning CoRR Eric Brochu, Vlad M. Cora, Nando de Freitas
2010	Misc	`conf`	A tutorial on stochastic approximation algorithms for training Restricted Boltzmann Machines and Deep Belief Nets. ITA Kevin Swersky, Bo Chen, Benjamin M. Marlin, Nando de Freitas
2010	A	`conf`	Inductive Principles for Restricted Boltzmann Machine Learning. AISTATS Benjamin M. Marlin, Kevin Swersky, Bo Chen, Nando de Freitas
2010	A	`conf`	Intracluster Moves for Constrained Discrete-Space MCMC. UAI Firas Hamze, Nando de Freitas
2010	J	`jnl`	Portfolio Allocation for Bayesian Optimization CoRR Eric Brochu, Matthew W. Hoffman, Nando de Freitas
2009	J	`jnl`	A Bayesian exploration-exploitation approach for optimal online sensing and planning with a visually guided mobile robot. Auton. Robots Ruben Martinez-Cantin, Nando de Freitas, Eric Brochu, José A. Castellanos, Arnaud Doucet
2009	A	`conf`	An Expectation Maximization Algorithm for Continuous Markov Decision Processes with Arbitrary Reward. AISTATS Matthew Hoffman, Nando de Freitas, Arnaud Doucet, Jan Peters
2009	Misc	`conf`	Inference and Learning for Active Sensing, Experimental Design and Control. IbPRIA Hendrik Kück, Matt Hoffman, Arnaud Doucet, Nando de Freitas
2009	A	`conf`	New inference strategies for solving Markov Decision Processes using reversible jump MCMC. UAI Matthias Hoffman, Hendrik Kück, Nando de Freitas, Arnaud Doucet
2008	—	`conf`	An interior-point stochastic approximation method and an L1-regularized delta rule. NIPS Peter Carbonetto, Mark Schmidt, Nando de Freitas
2008	J	`jnl`	Learning to Recognize Objects with Little Supervision. Int. J. Comput. Vis. Peter Carbonetto, Gyuri Dorkó, Cordelia Schmid, Hendrik Kück, Nando de Freitas
2008	A*	`conf`	Target-directed attention: Sequential decision-making for gaze planning. ICRA Julia Vogel, Nando de Freitas
2007	—	`conf`	Active Policy Learning for Robot Planning and Exploration under Uncertainty. Robotics: Science and Systems Ruben Martinez-Cantin, Nando de Freitas, Arnaud Doucet, José A. Castellanos
2007	—	`conf`	Active Preference Learning with Discrete Choice Data. NIPS Eric Brochu, Nando de Freitas, Abhijeet Ghosh
2007	A*	`conf`	Analysis of Particle Methods for Simultaneous Robot Localization and Mapping and a New Algorithm: Marginal-SLAM. ICRA Ruben Martinez-Cantin, Nando de Freitas, José A. Castellanos
2007	—	`conf`	Bayesian Policy Learning with Trans-Dimensional MCMC. NIPS Matt Hoffman, Arnaud Doucet, Nando de Freitas, Ajay Jasra
2007	A	`conf`	Large-Flip Importance Sampling. UAI Firas Hamze, Nando de Freitas
2007	—	`conf`	Preference galleries for material design. SIGGRAPH Posters Eric Brochu, Abhijeet Ghosh, Nando de Freitas
2006	—	`conf`	A Semi-supervised Learning Approach to Object Recognition with Spatial Integration of Local Features and Segmentation Cues. Toward Category-Level Object Recognition Peter Carbonetto, Gyuri Dorkó, Cordelia Schmid, Hendrik Kück, Nando de Freitas
2006	—	`conf`	Conditional mean field. NIPS Peter Carbonetto, Nando de Freitas
2006	A*	`conf`	Fast particle smoothing: if I had a million particles. ICML Mike Klaas, Mark Briers, Nando de Freitas, Arnaud Doucet, Simon Maskell, Dustin Lang
2006	—	`conf`	Robust Visual Tracking for Multiple Targets. ECCV (4) Yizheng Cai, Nando de Freitas, James J. Little
2005	A*	`conf`	Fast Computational Methods for Visually Guided Robots. ICRA Maryam Mahdaviani, Nando de Freitas, Bob Fraser, Firas Hamze
2005	—	`conf`	Fast Krylov Methods for N-Body Learning. NIPS Nando de Freitas, Yang Wang, Maryam Mahdaviani, Dustin Lang
2005	A	`conf`	Fast maximum a-posteriori inference on Monte Carlo state spaces. AISTATS Mike Klaas, Dustin Lang, Nando de Freitas
2005	—	`conf`	Hot Coupling: A Particle Approach to Inference and Normalization on Pairwise Undirected Graphs. NIPS Firas Hamze, Nando de Freitas
2005	A	`conf`	Learning about Individuals from Group Statistics. UAI Nando de Freitas, Hendrik Kück
2005	A	`conf`	Nonparametric Bayesian Logic. UAI Peter Carbonetto, Jacek Kisynski, Nando de Freitas, David Poole
2005	A	`conf`	Toward Practical N2 Monte Carlo: the Marginal Particle Filter. UAI Mike Klaas, Nando de Freitas, Arnaud Doucet
2004	—	`conf`	A Boosted Particle Filter: Multitarget Detection and Tracking. ECCV (1) Kenji Okuma, Ali Taleghani, Nando de Freitas, James J. Little, David G. Lowe
2004	—	`conf`	A Constrained Semi-supervised Learning Approach to Data Association. ECCV (3) Hendrik Kück, Peter Carbonetto, Nando de Freitas
2004	—	`conf`	A Statistical Model for General Contextual Object Recognition. ECCV (1) Peter Carbonetto, Nando de Freitas, Kobus Barnard
2004	—	`conf`	Beat Tracking the Graphical Model Way. NIPS Dustin Lang, Nando de Freitas
2004	J	`jnl`	Diagnosis by a waiter and a Mars explorer. Proc. IEEE Nando de Freitas, Richard Dearden, Frank Hutter, Rubén Morales-Menéndez, Jim Mutch, David Poole
2004	A	`conf`	From Fields to Trees. UAI Firas Hamze, Nando de Freitas
2003	A	`conf`	A Blessing of Dimensionality: Measure Concentration and Probabilistic Inference. AISTATS Pinar Muyan, Nando de Freitas
2003	J	`jnl`	An Introduction to MCMC for Machine Learning. Mach. Learn. Christophe Andrieu, Nando de Freitas, Arnaud Doucet, Michael I. Jordan
2003	A	`conf`	Bayesian Feature Weighting for Unsupervised Learning, with Application to Object Recognition. AISTATS Paul Gustafson, Peter Carbonetto, Natalie Thompson, Nando de Freitas
2003	C	`conf`	Estimation and control of industrial processes with particle filters. ACC Rubén Morales-Menéndez, Nando de Freitas, David Poole
2003	J	`jnl`	Matching Words and Pictures. J. Mach. Learn. Res. Kobus Barnard, Pinar Duygulu, David A. Forsyth, Nando de Freitas, David M. Blei, Michael I. Jordan
2003	A	`conf`	The Sound of an Album Cover: A Probabilistic Approach to Multimedia. AISTATS Eric Brochu, Nando de Freitas, Kejie Bao
2002	—	`conf`	"Name That Song!" A Probabilistic Approach to Querying on Music and Text. NIPS Eric Brochu, Nando de Freitas
2002	—	`conf`	Real-Time Monitoring of Complex Industrial Processes with Particle Filters. NIPS Rubén Morales-Menéndez, Nando de Freitas, David Poole
2001	—	`ch.`	An Introduction to Sequential Monte Carlo Methods. Sequential Monte Carlo Methods in Practice Arnaud Doucet, Nando de Freitas, Neil J. Gordon
2001	—	`conf`	Rao-Blackwellised Particle Filtering via Data Augmentation. NIPS Christophe Andrieu, Nando de Freitas, Arnaud Doucet
2001	J	`jnl`	Robust Full Bayesian Learning for Radial Basis Networks. Neural Comput. Christophe Andrieu, Nando de Freitas, Arnaud Doucet
2001	—	`ch.`	Sequential Monte Carlo Methods for Neural Networks. Sequential Monte Carlo Methods in Practice Nando de Freitas, Christophe Andrieu, Pedro A. d. F. R. Højen-Sørensen, M. Niranjan, A. Gee
2001	—	`book`	Sequential Monte Carlo Methods in Practice Arnaud Doucet, Nando de Freitas, Neil J. Gordon
2001	A	`conf`	Variational MCMC. UAI Nando de Freitas, Pedro A. d. F. R. Højen-Sørensen, Stuart Russell
2000	A	`conf`	Rao-Blackwellised Particle Filtering for Dynamic Bayesian Networks. UAI Arnaud Doucet, Nando de Freitas, Kevin P. Murphy, Stuart Russell
2000	A	`conf`	Reversible Jump MCMC Simulated Annealing for Neural Networks. UAI Christophe Andrieu, Nando de Freitas, Arnaud Doucet
2000	Misc	`conf`	Sequential Monte Carlo for model selection and estimation of neural networks. ICASSP Christophe Andrieu, Nando de Freitas
2000	—	`conf`	The Unscented Particle Filter. NIPS Rudolph van der Merwe, Arnaud Doucet, Nando de Freitas, Eric A. Wan