Scott E. Reed

47 papers A* 11Misc 1Journal 25Unranked 9
YearRankTypeTitle / 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
RoboCat: A Self-Improving Generalist Agent for Robotic Manipulation.
Trans. Mach. Learn. Res.
Konstantinos Bousmalis, Giulia Vezzani, Dushyant Rao, Coline Manon Devin, Alex X. Lee, Maria Bauzá Villalonga, Todor Davchev, Yuxiang Zhou, Agrim Gupta, Akhil Raju, Antoine Laurens, Claudio Fantacci, Valentin Dalibard, Martina Zambelli, Murilo Fernandes Martins, Rugile Pevceviciute, Michiel Blokzijl, Misha Denil, Nathan Batchelor, Thomas Lampe, Emilio Parisotto, Konrad Zolna, Scott E. Reed, Sergio Gómez Colmenarejo, Jon Scholz, Abbas Abdolmaleki, Oliver Groth, Jean-Baptiste Regli, Oleg Sushkov, Thomas Rothörl, José Enrique Chen, Yusuf Aytar, Dave Barker, Joy Ortiz, Martin A. Riedmiller, Jost Tobias Springenberg, Raia Hadsell, Francesco Nori, Nicolas Heess
2023 J jnl
RoboCat: A Self-Improving Foundation Agent for Robotic Manipulation.
CoRR
Konstantinos Bousmalis, Giulia Vezzani, Dushyant Rao, Coline Devin, Alex X. Lee, Maria Bauzá, Todor Davchev, Yuxiang Zhou, Agrim Gupta, Akhil Raju, Antoine Laurens, Claudio Fantacci, Valentin Dalibard, Martina Zambelli, Murilo F. Martins, Rugile Pevceviciute, Michiel Blokzijl, Misha Denil, Nathan Batchelor, Thomas Lampe, Emilio Parisotto, Konrad Zolna, Scott E. Reed, Sergio Gómez Colmenarejo, Jon Scholz, Abbas Abdolmaleki, Oliver Groth, Jean-Baptiste Regli, Oleg Sushkov, Thomas Rothörl, José Enrique Chen, Yusuf Aytar, Dave Barker, Joy Ortiz, Martin A. Riedmiller, Jost Tobias Springenberg, Raia Hadsell, Francesco Nori, Nicolas Heess
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
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 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
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 — 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 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 — 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 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 — 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 A* conf
Neural Arithmetic Logic Units.
NeurIPS
Andrew Trask, Felix Hill, Scott E. Reed, Jack W. Rae, Chris Dyer, Phil Blunsom
2018 J jnl
Neural Arithmetic Logic Units.
CoRR
Andrew Trask, Felix Hill, Scott E. Reed, Jack W. Rae, Chris Dyer, Phil Blunsom
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 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
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
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 — 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
2016 — —
Deep Neural Networks for Visual Reasoning, Program Induction, and Text-to-Image Synthesis.
Scott E. Reed
2016 A* conf
Generative Adversarial Text to Image Synthesis.
ICML
Scott E. Reed, Zeynep Akata, Xinchen Yan, Lajanugen Logeswaran, Bernt Schiele, Honglak Lee
2016 J jnl
Generative Adversarial Text to Image Synthesis.
CoRR
Scott E. Reed, Zeynep Akata, Xinchen Yan, Lajanugen Logeswaran, Bernt Schiele, Honglak Lee
2016 A* conf
Learning Deep Representations of Fine-Grained Visual Descriptions.
CVPR
Scott E. Reed, Zeynep Akata, Honglak Lee, Bernt Schiele
2016 J jnl
Learning Deep Representations of Fine-grained Visual Descriptions.
CoRR
Scott E. Reed, Zeynep Akata, Bernt Schiele, Honglak Lee
2016 — conf
Learning What and Where to Draw.
NIPS
Scott E. Reed, Zeynep Akata, Santosh Mohan, Samuel Tenka, Bernt Schiele, Honglak Lee
2016 J jnl
Learning What and Where to Draw.
CoRR
Scott E. Reed, Zeynep Akata, Santosh Mohan, Samuel Tenka, Bernt Schiele, Honglak Lee
2016 A* conf
Neural Programmer-Interpreters.
ICLR
Scott E. Reed, Nando de Freitas
2016 — conf
SSD: Single Shot MultiBox Detector.
ECCV (1)
Wei Liu, Dragomir Anguelov, Dumitru Erhan, Christian Szegedy, Scott E. Reed, Cheng-Yang Fu, Alexander C. Berg
2016 J jnl
Weakly-supervised Disentangling with Recurrent Transformations for 3D View Synthesis.
CoRR
Jimei Yang, Scott E. Reed, Ming-Hsuan Yang, Honglak Lee
2015 — conf
Deep Visual Analogy-Making.
NIPS
Scott E. Reed, Yi Zhang, Yuting Zhang, Honglak Lee
2015 A* conf
Evaluation of output embeddings for fine-grained image classification.
CVPR
Zeynep Akata, Scott E. Reed, Daniel Walter, Honglak Lee, Bernt Schiele
2015 A* conf
Going deeper with convolutions.
CVPR
Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott E. Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, Andrew Rabinovich
2015 J jnl
SSD: Single Shot MultiBox Detector.
CoRR
Wei Liu, Dragomir Anguelov, Dumitru Erhan, Christian Szegedy, Scott E. Reed, Cheng-Yang Fu, Alexander C. Berg
2015 — conf
Training Deep Neural Networks on Noisy Labels with Bootstrapping.
ICLR (Workshop)
Scott E. Reed, Honglak Lee, Dragomir Anguelov, Christian Szegedy, Dumitru Erhan, Andrew Rabinovich
2015 — conf
Weakly-supervised Disentangling with Recurrent Transformations for 3D View Synthesis.
NIPS
Jimei Yang, Scott E. Reed, Ming-Hsuan Yang, Honglak Lee
2014 J jnl
Going Deeper with Convolutions.
CoRR
Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott E. Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, Andrew Rabinovich
2014 A* conf
Learning to Disentangle Factors of Variation with Manifold Interaction.
ICML
Scott E. Reed, Kihyuk Sohn, Yuting Zhang, Honglak Lee
2014 J jnl
Scalable, High-Quality Object Detection.
CoRR
Christian Szegedy, Scott E. Reed, Dumitru Erhan, Dragomir Anguelov