Karol Gregor

According to our database, Karol Gregor authored at least 34 papers between 2009 and 2024.

Collaborative distances:

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

2024

Scaling Instructable Agents Across Many Simulated Worlds.

SIMA Team, Maria Abi Raad, Arun Ahuja, Catarina Barros, Frederic Besse, Andrew Bolt, Adrian Bolton, Bethanie Brownfield, Gavin Buttimore, Max Cant, Sarah Chakera, Stephanie C. Y. Chan, Jeff Clune, Adrian Collister, Vikki Copeman, Alex Cullum, Ishita Dasgupta, Dario de Cesare, Julia Di Trapani, Yani Donchev, Emma Dunleavy, Martin Engelcke, Ryan Faulkner, Frankie Garcia, Charles Gbadamosi, Zhitao Gong, Lucy Gonzalez, Kshitij Gupta, Karol Gregor, Arne Olav Hallingstad, Tim Harley, Sam Haves, Felix Hill, Ed Hirst, Drew A. Hudson, Jony Hudson, Steph Hughes-Fitt, Danilo J. Rezende, Mimi Jasarevic, Laura Kampis, Nan Rosemary Ke, Thomas Keck, Junkyung Kim, Oscar Knagg, Kavya Kopparapu, Andrew K. Lampinen, Shane Legg, Alexander Lerchner, Marjorie Limont, Yulan Liu, Maria Loks-Thompson, Joseph Marino, Kathryn Martin Cussons, Loic Matthey, Siobhan Mcloughlin, Piermaria Mendolicchio, Hamza Merzic, Anna Mitenkova, Alexandre Moufarek, Valéria Oliveira, Yanko Gitahy Oliveira, Hannah Openshaw, Renke Pan, Aneesh Pappu, Alex Platonov, Ollie Purkiss, David P. Reichert, John Reid, Pierre Harvey Richemond, Tyson Roberts, Giles Ruscoe, Jaume Sanchez Elias, Tasha Sandars, Daniel P. Sawyer, Tim Scholtes, Guy Simmons, Daniel Slater, Hubert Soyer, Heiko Strathmann, Peter Stys, Allison C. Tam, Denis Teplyashin, Tayfun Terzi, Davide Vercelli, Bojan Vujatovic, Marcus Wainwright, Jane X. Wang, Zhengdong Wang, Daan Wierstra, Duncan Williams, Nathaniel Wong, Sarah York, Nick Young

CoRR, 2024

2023

Human-Timescale Adaptation in an Open-Ended Task Space.

Adaptive Agent Team, Jakob Bauer, Kate Baumli, Satinder Baveja, Feryal M. P. Behbahani, Avishkar Bhoopchand, Nathalie Bradley-Schmieg, Michael Chang, Natalie Clay, Adrian Collister, Vibhavari Dasagi, Lucy Gonzalez, Karol Gregor, Edward Hughes, Sheleem Kashem, Maria Loks-Thompson, Hannah Openshaw, Jack Parker-Holder, Shreya Pathak, Nicolas Perez Nieves, Nemanja Rakicevic, Tim Rocktäschel, Yannick Schroecker, Jakub Sygnowski, Karl Tuyls, Sarah York, Alexander Zacherl, Lei Zhang

CoRR, 2023

Human-Timescale Adaptation in an Open-Ended Task Space.

Jakob Bauer, Kate Baumli, Feryal M. P. Behbahani, Avishkar Bhoopchand, Nathalie Bradley-Schmieg, Michael Chang, Natalie Clay, Adrian Collister, Vibhavari Dasagi, Lucy Gonzalez, Karol Gregor, Edward Hughes, Sheleem Kashem, Maria Loks-Thompson, Hannah Openshaw, Jack Parker-Holder, Shreya Pathak, Nicolas Perez Nieves, Nemanja Rakicevic, Tim Rocktäschel, Yannick Schroecker, Satinder Singh, Jakub Sygnowski, Karl Tuyls, Sarah York, Alexander Zacherl, Lei M. Zhang

Proceedings of the International Conference on Machine Learning, 2023

2021

Self-Organizing Intelligent Matter: A blueprint for an AI generating algorithm.

Karol Gregor, Frederic Besse

CoRR, 2021

2020

Finding online neural update rules by learning to remember.

Karol Gregor

CoRR, 2020

Causally Correct Partial Models for Reinforcement Learning.

Danilo J. Rezende, Ivo Danihelka, George Papamakarios, Nan Rosemary Ke, Ray Jiang, Theophane Weber, Karol Gregor, Hamza Merzic, Fabio Viola, Jane Wang, Jovana Mitrovic, Frederic Besse, Ioannis Antonoglou, Lars Buesing

CoRR, 2020

2019

Shaping Belief States with Generative Environment Models for RL.

Karol Gregor, Danilo Jimenez Rezende, Frederic Besse, Yan Wu, Hamza Merzic, Aäron van den Oord

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

An Investigation of Model-Free Planning.

Arthur Guez, Mehdi Mirza, Karol Gregor, Rishabh Kabra, Sébastien Racanière, Theophane Weber, David Raposo, Adam Santoro, Laurent Orseau, Tom Eccles, Greg Wayne, David Silver, Timothy P. Lillicrap

Proceedings of the 36th International Conference on Machine Learning, 2019

Temporal Difference Variational Auto-Encoder.

Karol Gregor, George Papamakarios, Frederic Besse, Lars Buesing, Theophane Weber

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

2018

Temporal Difference Variational Auto-Encoder.

Karol Gregor, Frederic Besse

CoRR, 2018

Learning and Querying Fast Generative Models for Reinforcement Learning.

Lars Buesing, Theophane Weber, Sébastien Racanière, S. M. Ali Eslami, Danilo Jimenez Rezende, David P. Reichert, Fabio Viola, Frederic Besse, Karol Gregor, Demis Hassabis, Daan Wierstra

CoRR, 2018

Learning Attractor Dynamics for Generative Memory.

Yan Wu, Gregory Wayne, Karol Gregor, Timothy P. Lillicrap

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2017

Variational Intrinsic Control.

Karol Gregor, Danilo Jimenez Rezende, Daan Wierstra

Proceedings of the 5th International Conference on Learning Representations, 2017

2016

Neural Autoregressive Distribution Estimation.

Benigno Uria, Marc-Alexandre Côté, Karol Gregor, Iain Murray, Hugo Larochelle

J. Mach. Learn. Res., 2016

What is the Best Feature Learning Procedure in Hierarchical Recognition Architectures?

Kevin Jarrett, Koray Kavukcuoglu, Karol Gregor, Yann LeCun

CoRR, 2016

Towards Conceptual Compression.

Karol Gregor, Frederic Besse, Danilo Jimenez Rezende, Ivo Danihelka, Daan Wierstra

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

One-Shot Generalization in Deep Generative Models.

Danilo Jimenez Rezende, Shakir Mohamed, Ivo Danihelka, Karol Gregor, Daan Wierstra

Proceedings of the 33nd International Conference on Machine Learning, 2016

2015

Towards Principled Unsupervised Learning.

Ilya Sutskever, Rafal Józefowicz, Karol Gregor, Danilo Jimenez Rezende, Timothy P. Lillicrap, Oriol Vinyals

CoRR, 2015

DRAW: A Recurrent Neural Network For Image Generation.

Karol Gregor, Ivo Danihelka, Alex Graves, Daan Wierstra

CoRR, 2015

Universal Value Function Approximators.

Tom Schaul, Daniel Horgan, Karol Gregor, David Silver

Proceedings of the 32nd International Conference on Machine Learning, 2015

DRAW: A Recurrent Neural Network For Image Generation.

Karol Gregor, Ivo Danihelka, Alex Graves, Danilo Jimenez Rezende, Daan Wierstra

Proceedings of the 32nd International Conference on Machine Learning, 2015

MADE: Masked Autoencoder for Distribution Estimation.

Mathieu Germain, Karol Gregor, Iain Murray, Hugo Larochelle

Proceedings of the 32nd International Conference on Machine Learning, 2015

2014

Neural Variational Inference and Learning in Belief Networks.

Andriy Mnih, Karol Gregor

Proceedings of the 31th International Conference on Machine Learning, 2014

Deep AutoRegressive Networks.

Karol Gregor, Ivo Danihelka, Andriy Mnih, Charles Blundell, Daan Wierstra

Proceedings of the 31th International Conference on Machine Learning, 2014

2013

Deep AutoRegressive Networks.

Karol Gregor, Andriy Mnih, Daan Wierstra

CoRR, 2013

2012

A lattice filter model of the visual pathway.

Karol Gregor, Dmitri B. Chklovskii

Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Fast Approximations to Structured Sparse Coding and Applications to Object Classification.

Arthur Szlam, Karol Gregor, Yann LeCun

Proceedings of the Computer Vision - ECCV 2012, 2012

2011

Learning Representations by Maximizing Compression

Karol Gregor, Yann LeCun

CoRR, 2011

Efficient Learning of Sparse Invariant Representations

Karol Gregor, Yann LeCun

CoRR, 2011

Structured sparse coding via lateral inhibition.

Arthur Szlam, Karol Gregor, Yann LeCun

Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

2010

Emergence of Complex-Like Cells in a Temporal Product Network with Local Receptive Fields

Karol Gregor, Yann LeCun

CoRR, 2010

Learning Convolutional Feature Hierarchies for Visual Recognition.

Koray Kavukcuoglu, Pierre Sermanet, Y-Lan Boureau, Karol Gregor, Michaël Mathieu, Yann LeCun

Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

Learning Fast Approximations of Sparse Coding.

Karol Gregor, Yann LeCun

Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010

2009

Behavior and performance of the deep belief networks on image classification

Karol Gregor, Gregory Griffin

CoRR, 2009