Simon Osindero

According to our database, Simon Osindero authored at least 57 papers between 2002 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Genie: Generative Interactive Environments.

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

CoRR, 2024

2023

Generative agent-based modeling with actions grounded in physical, social, or digital space using Concordia.

Alexander Sasha Vezhnevets, John P. Agapiou, Avia Aharon, Ron Ziv, Jayd Matyas, Edgar A. Duéñez-Guzmán, William A. Cunningham, Simon Osindero, Danny Karmon, Joel Z. Leibo

CoRR, 2023

Solving MaxSAT with Matrix Multiplication.

David Warde-Farley, Vinod Nair, Yujia Li, Ivan Lobov, Felix Gimeno, Simon Osindero

CoRR, 2023

Promptbreeder: Self-Referential Self-Improvement Via Prompt Evolution.

Chrisantha Fernando, Dylan Banarse, Henryk Michalewski, Simon Osindero, Tim Rocktäschel

CoRR, 2023

Perception Test: A Diagnostic Benchmark for Multimodal Video Models.

Viorica Patraucean, Lucas Smaira, Ankush Gupta, Adrià Recasens, Larisa Markeeva, Dylan Banarse, Skanda Koppula, Joseph Heyward, Mateusz Malinowski, Yi Yang, Carl Doersch, Tatiana Matejovicova, Yury Sulsky, Antoine Miech, Alexandre Fréchette, Hanna Klimczak, Raphael Koster, Junlin Zhang, Stephanie Winkler, Yusuf Aytar, Simon Osindero, Dima Damen, Andrew Zisserman, João Carreira

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

Training Compute-Optimal Large Language Models.

Jordan Hoffmann, Sebastian Borgeaud, Arthur Mensch, Elena Buchatskaya, Trevor Cai, Eliza Rutherford, Diego de Las Casas, Lisa Anne Hendricks, Johannes Welbl, Aidan Clark, Tom Hennigan, Eric Noland, Katie Millican, George van den Driessche, Bogdan Damoc, Aurelia Guy, Simon Osindero, Karen Simonyan, Erich Elsen, Jack W. Rae, Oriol Vinyals, Laurent Sifre

CoRR, 2022

Retrieval-Augmented Reinforcement Learning.

Anirudh Goyal, Abram L. Friesen, Andrea Banino, Theophane Weber, Nan Rosemary Ke, Adrià Puigdomènech Badia, Arthur Guez, Mehdi Mirza, Ksenia Konyushkova, Michal Valko, Simon Osindero, Timothy P. Lillicrap, Nicolas Heess, Charles Blundell

CoRR, 2022

Unified Scaling Laws for Routed Language Models.

Aidan Clark, Diego de Las Casas, Aurelia Guy, Arthur Mensch, Michela Paganini, Jordan Hoffmann, Bogdan Damoc, Blake A. Hechtman, Trevor Cai, Sebastian Borgeaud, George van den Driessche, Eliza Rutherford, Tom Hennigan, Matthew J. Johnson, Katie Millican, Albin Cassirer, Chris Jones, Elena Buchatskaya, David Budden, Laurent Sifre, Simon Osindero, Oriol Vinyals, Jack W. Rae, Erich Elsen, Koray Kavukcuoglu, Karen Simonyan

CoRR, 2022

An empirical analysis of compute-optimal large language model training.

Jordan Hoffmann, Sebastian Borgeaud, Arthur Mensch, Elena Buchatskaya, Trevor Cai, Eliza Rutherford, Diego de Las Casas, Lisa Anne Hendricks, Johannes Welbl, Aidan Clark, Tom Hennigan, Eric Noland, Katherine Millican, George van den Driessche, Bogdan Damoc, Aurelia Guy, Simon Osindero, Karen Simonyan, Erich Elsen, Oriol Vinyals, Jack W. Rae, Laurent Sifre

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Retrieval-Augmented Reinforcement Learning.

Anirudh Goyal, Abram L. Friesen, Andrea Banino, Theophane Weber, Nan Rosemary Ke, Adrià Puigdomènech Badia, Arthur Guez, Mehdi Mirza, Peter C. Humphreys, Ksenia Konyushkova, Michal Valko, Simon Osindero, Timothy P. Lillicrap, Nicolas Heess, Charles Blundell

Proceedings of the International Conference on Machine Learning, 2022

Model-Value Inconsistency as a Signal for Epistemic Uncertainty.

Angelos Filos, Eszter Vértes, Zita Marinho, Gregory Farquhar, Diana Borsa, Abram L. Friesen, Feryal M. P. Behbahani, Tom Schaul, André Barreto, Simon Osindero

Proceedings of the International Conference on Machine Learning, 2022

Unified Scaling Laws for Routed Language Models.

Aidan Clark, Diego de Las Casas, Aurelia Guy, Arthur Mensch, Michela Paganini, Jordan Hoffmann, Bogdan Damoc, Blake A. Hechtman, Trevor Cai, Sebastian Borgeaud, George van den Driessche, Eliza Rutherford, Tom Hennigan, Matthew J. Johnson, Albin Cassirer, Chris Jones, Elena Buchatskaya, David Budden, Laurent Sifre, Simon Osindero, Oriol Vinyals, Marc'Aurelio Ranzato, Jack W. Rae, Erich Elsen, Koray Kavukcuoglu, Karen Simonyan

Proceedings of the International Conference on Machine Learning, 2022

Improving Language Models by Retrieving from Trillions of Tokens.

Sebastian Borgeaud, Arthur Mensch, Jordan Hoffmann, Trevor Cai, Eliza Rutherford, Katie Millican, George van den Driessche, Jean-Baptiste Lespiau, Bogdan Damoc, Aidan Clark, Diego de Las Casas, Aurelia Guy, Jacob Menick, Roman Ring, Tom Hennigan, Saffron Huang, Loren Maggiore, Chris Jones, Albin Cassirer, Andy Brock, Michela Paganini, Geoffrey Irving, Oriol Vinyals, Simon Osindero, Karen Simonyan, Jack W. Rae, Erich Elsen, Laurent Sifre

Proceedings of the International Conference on Machine Learning, 2022

CLIP-CLOP: CLIP-Guided Collage and Photomontage.

Piotr Mirowski, Dylan Banarse, Mateusz Malinowski, Simon Osindero, Chrisantha Fernando

Proceedings of the 13th International Conference on Computational Creativity, Bozen-Bolzano, Italy, June 27, 2022

2021

Scaling Language Models: Methods, Analysis & Insights from Training Gopher.

Jack W. Rae, Sebastian Borgeaud, Trevor Cai, Katie Millican, Jordan Hoffmann, H. Francis Song, John Aslanides, Sarah Henderson, Roman Ring, Susannah Young, Eliza Rutherford, Tom Hennigan, Jacob Menick, Albin Cassirer, Richard Powell, George van den Driessche, Lisa Anne Hendricks, Maribeth Rauh, Po-Sen Huang, Amelia Glaese, Johannes Welbl, Sumanth Dathathri, Saffron Huang, Jonathan Uesato, John Mellor, Irina Higgins, Antonia Creswell, Nat McAleese, Amy Wu, Erich Elsen, Siddhant M. Jayakumar, Elena Buchatskaya, David Budden, Esme Sutherland, Karen Simonyan, Michela Paganini, Laurent Sifre, Lena Martens, Xiang Lorraine Li, Adhiguna Kuncoro, Aida Nematzadeh, Elena Gribovskaya, Domenic Donato, Angeliki Lazaridou, Arthur Mensch, Jean-Baptiste Lespiau, Maria Tsimpoukelli, Nikolai Grigorev, Doug Fritz, Thibault Sottiaux, Mantas Pajarskas, Toby Pohlen, Zhitao Gong, Daniel Toyama, Cyprien de Masson d'Autume, Yujia Li, Tayfun Terzi, Vladimir Mikulik, Igor Babuschkin, Aidan Clark, Diego de Las Casas, Aurelia Guy, Chris Jones, James Bradbury, Matthew J. Johnson, Blake A. Hechtman, Laura Weidinger, Iason Gabriel, William Isaac, Edward Lockhart, Simon Osindero, Laura Rimell, Chris Dyer, Oriol Vinyals, Kareem Ayoub, Jeff Stanway, Lorrayne Bennett, Demis Hassabis, Koray Kavukcuoglu, Geoffrey Irving

CoRR, 2021

Generative Art Using Neural Visual Grammars and Dual Encoders.

Chrisantha Fernando, S. M. Ali Eslami, Jean-Baptiste Alayrac, Piotr Mirowski, Dylan Banarse, Simon Osindero

CoRR, 2021

Entropic Desired Dynamics for Intrinsic Control.

Steven Hansen, Guillaume Desjardins, Kate Baumli, David Warde-Farley, Nicolas Heess, Simon Osindero, Volodymyr Mnih

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Practical Real Time Recurrent Learning with a Sparse Approximation.

Jacob Menick, Erich Elsen, Utku Evci, Simon Osindero, Karen Simonyan, Alex Graves

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

Contrastive Topographic Models: Energy-based density models applied to the understanding of sensory coding and cortical topography.

Simon Osindero

CoRR, 2020

From Language Games to Drawing Games.

Chrisantha Fernando, Daria Zenkova, Stanislav Nikolov, Simon Osindero

CoRR, 2020

AlgebraNets.

Jordan Hoffmann, Simon Schmitt, Simon Osindero, Karen Simonyan, Erich Elsen

CoRR, 2020

A Practical Sparse Approximation for Real Time Recurrent Learning.

Jacob Menick, Erich Elsen, Utku Evci, Simon Osindero, Karen Simonyan, Alex Graves

CoRR, 2020

Top-KAST: Top-K Always Sparse Training.

Siddhant M. Jayakumar, Razvan Pascanu, Jack W. Rae, Simon Osindero, Erich Elsen

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Small Data, Big Decisions: Model Selection in the Small-Data Regime.

Jörg Bornschein, Francesco Visin, Simon Osindero

Proceedings of the 37th International Conference on Machine Learning, 2020

Multiplicative Interactions and Where to Find Them.

Siddhant M. Jayakumar, Wojciech M. Czarnecki, Jacob Menick, Jonathan Schwarz, Jack W. Rae, Simon Osindero, Yee Whye Teh, Tim Harley, Razvan Pascanu

Proceedings of the 8th International Conference on Learning Representations, 2020

Meta-Learning Deep Energy-Based Memory Models.

Sergey Bartunov, Jack W. Rae, Simon Osindero, Timothy P. Lillicrap

Proceedings of the 8th International Conference on Learning Representations, 2020

2019

A Deep Neural Network's Loss Surface Contains Every Low-dimensional Pattern.

Wojciech Marian Czarnecki, Simon Osindero, Razvan Pascanu, Max Jaderberg

CoRR, 2019

Adapting Behaviour for Learning Progress.

Tom Schaul, Diana Borsa, David Ding, David Szepesvari, Georg Ostrovski, Will Dabney, Simon Osindero

CoRR, 2019

Meta-learning of Sequential Strategies.

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

CoRR, 2019

Meta-Learning with Latent Embedding Optimization.

Andrei A. Rusu, Dushyant Rao, Jakub Sygnowski, Oriol Vinyals, Razvan Pascanu, Simon Osindero, Raia Hadsell

Proceedings of the 7th International Conference on Learning Representations, 2019

Distilling Policy Distillation.

Wojciech M. Czarnecki, Razvan Pascanu, Simon Osindero, Siddhant M. Jayakumar, Grzegorz Swirszcz, Max Jaderberg

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018

Kickstarting Deep Reinforcement Learning.

Simon Schmitt, Jonathan J. Hudson, Augustin Zídek, Simon Osindero, Carl Doersch, Wojciech M. Czarnecki, Joel Z. Leibo, Heinrich Küttler, Andrew Zisserman, Karen Simonyan, S. M. Ali Eslami

CoRR, 2018

Mix & Match Agent Curricula for Reinforcement Learning.

Wojciech Marian Czarnecki, Siddhant M. Jayakumar, Max Jaderberg, Leonard Hasenclever, Yee Whye Teh, Nicolas Heess, Simon Osindero, Razvan Pascanu

Proceedings of the 35th International Conference on Machine Learning, 2018

Meta-learning by the Baldwin effect.

Chrisantha Fernando, Jakub Sygnowski, Simon Osindero, Jane Wang, Tom Schaul, Denis Teplyashin, Pablo Sprechmann, Alexander Pritzel, Andrei A. Rusu

Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2018

Massively Parallel Video Networks.

João Carreira, Viorica Patraucean, Laurent Mazaré, Andrew Zisserman, Simon Osindero

Proceedings of the Computer Vision - ECCV 2018, 2018

2017

Beautiful and Damned. Combined Effect of Content Quality and Social Ties on User Engagement.

Luca Maria Aiello, Rossano Schifanella, Miriam Redi, Stacey Svetlichnaya, Frank Liu, Simon Osindero

IEEE Trans. Knowl. Data Eng., 2017

Population Based Training of Neural Networks.

Max Jaderberg, Valentin Dalibard, Simon Osindero, Wojciech M. Czarnecki, Jeff Donahue, Ali Razavi, Oriol Vinyals, Tim Green, Iain Dunning, Karen Simonyan, Chrisantha Fernando, Koray Kavukcuoglu

CoRR, 2017

Sobolev Training for Neural Networks.

Wojciech M. Czarnecki, Simon Osindero, Max Jaderberg, Grzegorz Swirszcz, Razvan Pascanu

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

FeUdal Networks for Hierarchical Reinforcement Learning.

Alexander Sasha Vezhnevets, Simon Osindero, Tom Schaul, Nicolas Heess, Max Jaderberg, David Silver, Koray Kavukcuoglu

Proceedings of the 34th International Conference on Machine Learning, 2017

Decoupled Neural Interfaces using Synthetic Gradients.

Max Jaderberg, Wojciech Marian Czarnecki, Simon Osindero, Oriol Vinyals, Alex Graves, David Silver, Koray Kavukcuoglu

Proceedings of the 34th International Conference on Machine Learning, 2017

Understanding Synthetic Gradients and Decoupled Neural Interfaces.

Wojciech Marian Czarnecki, Grzegorz Swirszcz, Max Jaderberg, Simon Osindero, Oriol Vinyals, Koray Kavukcuoglu

Proceedings of the 34th International Conference on Machine Learning, 2017

2016

Decoupled Neural Interfaces using Synthetic Gradients.

Max Jaderberg, Wojciech Marian Czarnecki, Simon Osindero, Oriol Vinyals, Alex Graves, Koray Kavukcuoglu

CoRR, 2016

Strategic Attentive Writer for Learning Macro-Actions.

Alexander Vezhnevets, Volodymyr Mnih, Simon Osindero, Alex Graves, Oriol Vinyals, John P. Agapiou, Koray Kavukcuoglu

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

What Makes Photo Cultures Different?

Miriam Redi, Damon Crockett, Lev Manovich, Simon Osindero

Proceedings of the 2016 ACM Conference on Multimedia Conference, 2016

Cross-Dimensional Weighting for Aggregated Deep Convolutional Features.

Yannis Kalantidis, Clayton Mellina, Simon Osindero

Proceedings of the Computer Vision - ECCV 2016 Workshops, 2016

Recursive Recurrent Nets with Attention Modeling for OCR in the Wild.

Chen-Yu Lee, Simon Osindero

Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition, 2016

2014

Conditional Generative Adversarial Nets.

Mehdi Mirza, Simon Osindero

CoRR, 2014

2007

Modeling image patches with a directed hierarchy of Markov random fields.

Simon Osindero, Geoffrey E. Hinton

Proceedings of the Advances in Neural Information Processing Systems 20, 2007

2006

Topographic Product Models Applied to Natural Scene Statistics.

Simon Osindero, Max Welling, Geoffrey E. Hinton

Neural Comput., 2006

A Fast Learning Algorithm for Deep Belief Nets.

Geoffrey E. Hinton, Simon Osindero, Yee Whye Teh

Neural Comput., 2006

Unsupervised Discovery of Nonlinear Structure Using Contrastive Backpropagation.

Geoffrey E. Hinton, Simon Osindero, Max Welling, Yee Whye Teh

Cogn. Sci., 2006

Combining discriminative features to infer complex trajectories.

David A. Ross, Simon Osindero, Richard S. Zemel

Proceedings of the Machine Learning, 2006

2005

An Alternative Infinite Mixture Of Gaussian Process Experts.

Edward Meeds, Simon Osindero

Proceedings of the Advances in Neural Information Processing Systems 18 [Neural Information Processing Systems, 2005

Learning Causally Linked Markov Random Fields.

Geoffrey E. Hinton, Simon Osindero, Kejie Bao

Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, 2005

2004

Contrastive topographic models.

Simon Kayode Osindero

PhD thesis, 2004

2003

Energy-Based Models for Sparse Overcomplete Representations.

Yee Whye Teh, Max Welling, Simon Osindero, Geoffrey E. Hinton

J. Mach. Learn. Res., 2003

2002

Learning Sparse Topographic Representations with Products of Student-t Distributions.

Max Welling, Geoffrey E. Hinton, Simon Osindero

Proceedings of the Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, 2002