Behavior and performance of the deep belief networks on image classification - Karol Gregor; Gregory Griffin (CoRR, 2009)

Learning Fast Approximations of Sparse Coding. - Karol Gregor; Yann LeCun (ICML, 2010)

Learning Convolutional Feature Hierarchies for Visual Recognition. - Koray Kavukcuoglu; Pierre Sermanet; Y-Lan Boureau; Karol Gregor; Michaël Mathieu; Yann LeCun (NIPS, 2010)

Emergence of Complex-Like Cells in a Temporal Product Network with Local Receptive Fields - Karol Gregor; Yann LeCun (CoRR, 2010)

Structured sparse coding via lateral inhibition. - Arthur Szlam; Karol Gregor; Yann LeCun (NIPS, 2011)

Efficient Learning of Sparse Invariant Representations - Karol Gregor; Yann LeCun (CoRR, 2011)

Learning Representations by Maximizing Compression - Karol Gregor; Yann LeCun (CoRR, 2011)

Fast Approximations to Structured Sparse Coding and Applications to Object Classification. - Arthur Szlam; Karol Gregor; Yann LeCun (ECCV (5), 2012)

A lattice filter model of the visual pathway. - Karol Gregor; Dmitri B. Chklovskii (NIPS, 2012)

Deep AutoRegressive Networks. - Karol Gregor; Andriy Mnih; Daan Wierstra (CoRR, 2013)

Deep AutoRegressive Networks. - Karol Gregor; Ivo Danihelka; Andriy Mnih; Charles Blundell; Daan Wierstra (ICML, 2014)

Neural Variational Inference and Learning in Belief Networks. - Andriy Mnih; Karol Gregor (ICML, 2014)

MADE: Masked Autoencoder for Distribution Estimation. - Mathieu Germain; Karol Gregor; Iain Murray 001; Hugo Larochelle (ICML, 2015)

DRAW: A Recurrent Neural Network For Image Generation. - Karol Gregor; Ivo Danihelka; Alex Graves; Danilo Jimenez Rezende; Daan Wierstra (ICML, 2015)

Universal Value Function Approximators. - Tom Schaul; Daniel Horgan; Karol Gregor; David Silver (ICML, 2015)

DRAW: A Recurrent Neural Network For Image Generation. - Karol Gregor; Ivo Danihelka; Alex Graves; Daan Wierstra (CoRR, 2015)

Towards Principled Unsupervised Learning. - Ilya Sutskever; Rafal Józefowicz; Karol Gregor; Danilo Jimenez Rezende; Timothy P. Lillicrap; Oriol Vinyals (CoRR, 2015)

One-Shot Generalization in Deep Generative Models. - Danilo Jimenez Rezende; Shakir Mohamed; Ivo Danihelka; Karol Gregor; Daan Wierstra (ICML, 2016)

Towards Conceptual Compression. - Karol Gregor; Frederic Besse; Danilo Jimenez Rezende; Ivo Danihelka; Daan Wierstra (NIPS, 2016)

What is the Best Feature Learning Procedure in Hierarchical Recognition Architectures? - Kevin Jarrett; Koray Kavukcuoglu; Karol Gregor; Yann LeCun (CoRR, 2016)

Neural Autoregressive Distribution Estimation. - Benigno Uria; Marc-Alexandre Côté; Karol Gregor; Iain Murray 001; Hugo Larochelle (J. Mach. Learn. Res., 2016)

Variational Intrinsic Control. - Karol Gregor; Danilo Jimenez Rezende; Daan Wierstra (ICLR (Workshop), 2017)

Learning Attractor Dynamics for Generative Memory. - Yan Wu 010; Gregory Wayne; Karol Gregor; Timothy P. Lillicrap (NeurIPS, 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)

Temporal Difference Variational Auto-Encoder. - Karol Gregor; Frederic Besse (CoRR, 2018)

Temporal Difference Variational Auto-Encoder. - Karol Gregor; George Papamakarios; Frederic Besse; Lars Buesing; Theophane Weber (ICLR, 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; et al. (ICML, 2019)

Shaping Belief States with Generative Environment Models for RL. - Karol Gregor; Danilo Jimenez Rezende; Frederic Besse; Yan Wu 010; Hamza Merzic; Aäron van den Oord (NeurIPS, 2019)

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 001; Jovana Mitrovic; Frederic Besse; et al. (CoRR, 2020)

Finding online neural update rules by learning to remember. - Karol Gregor (CoRR, 2020)

Self-Organizing Intelligent Matter: A blueprint for an AI generating algorithm. - Karol Gregor; Frederic Besse (CoRR, 2021)

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 001; et al. (ICML, 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; et al. (CoRR, 2023)

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; et al. (CoRR, 2024)