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2020 – today
- 2023
[c18]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:
Human-Timescale Adaptation in an Open-Ended Task Space. ICML 2023: 1887-1935- [i24]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:
Human-Timescale Adaptation in an Open-Ended Task Space. CoRR abs/2301.07608 (2023) - 2021
- [i23]Karol Gregor, Frederic Besse:
Self-Organizing Intelligent Matter: A blueprint for an AI generating algorithm. CoRR abs/2101.07627 (2021) - 2020
- [i22]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:
Causally Correct Partial Models for Reinforcement Learning. CoRR abs/2002.02836 (2020) - [i21]Karol Gregor:
Finding online neural update rules by learning to remember. CoRR abs/2003.03124 (2020)
2010 – 2019
- 2019
- [c17]Karol Gregor, George Papamakarios, Frederic Besse, Lars Buesing, Theophane Weber:
Temporal Difference Variational Auto-Encoder. ICLR 2019 - [c16]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:
An Investigation of Model-Free Planning. ICML 2019: 2464-2473 - [c15]Karol Gregor, Danilo Jimenez Rezende, Frederic Besse, Yan Wu, Hamza Merzic, Aäron van den Oord:
Shaping Belief States with Generative Environment Models for RL. NeurIPS 2019: 13475-13487 - [i20]Arthur Guez, Mehdi Mirza, Karol Gregor, Rishabh Kabra, Sébastien Racanière, Théophane Weber, David Raposo, Adam Santoro, Laurent Orseau, Tom Eccles, Greg Wayne, David Silver, Timothy P. Lillicrap:
An investigation of model-free planning. CoRR abs/1901.03559 (2019) - [i19]Karol Gregor, Danilo Jimenez Rezende, Frederic Besse, Yan Wu, Hamza Merzic, Aäron van den Oord:
Shaping Belief States with Generative Environment Models for RL. CoRR abs/1906.09237 (2019) - 2018
- [c14]Yan Wu, Gregory Wayne, Karol Gregor, Timothy P. Lillicrap:
Learning Attractor Dynamics for Generative Memory. NeurIPS 2018: 9401-9410 - [i18]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:
Learning and Querying Fast Generative Models for Reinforcement Learning. CoRR abs/1802.03006 (2018) - [i17]Karol Gregor, Frederic Besse:
Temporal Difference Variational Auto-Encoder. CoRR abs/1806.03107 (2018) - [i16]Yan Wu, Greg Wayne, Karol Gregor, Timothy P. Lillicrap:
Learning Attractor Dynamics for Generative Memory. CoRR abs/1811.09556 (2018) - 2017
- [c13]Karol Gregor, Danilo Jimenez Rezende, Daan Wierstra:
Variational Intrinsic Control. ICLR (Workshop) 2017 - 2016
- [j1]Benigno Uria, Marc-Alexandre Côté, Karol Gregor, Iain Murray, Hugo Larochelle:
Neural Autoregressive Distribution Estimation. J. Mach. Learn. Res. 17: 205:1-205:37 (2016) - [c12]Danilo Jimenez Rezende, Shakir Mohamed, Ivo Danihelka, Karol Gregor, Daan Wierstra:
One-Shot Generalization in Deep Generative Models. ICML 2016: 1521-1529 - [c11]Karol Gregor, Frederic Besse, Danilo Jimenez Rezende, Ivo Danihelka, Daan Wierstra:
Towards Conceptual Compression. NIPS 2016: 3549-3557 - [i15]Danilo Jimenez Rezende, Shakir Mohamed, Ivo Danihelka, Karol Gregor, Daan Wierstra:
One-Shot Generalization in Deep Generative Models. CoRR abs/1603.05106 (2016) - [i14]Karol Gregor, Frederic Besse, Danilo Jimenez Rezende, Ivo Danihelka, Daan Wierstra:
Towards Conceptual Compression. CoRR abs/1604.08772 (2016) - [i13]Benigno Uria, Marc-Alexandre Côté, Karol Gregor, Iain Murray, Hugo Larochelle:
Neural Autoregressive Distribution Estimation. CoRR abs/1605.02226 (2016) - [i12]Kevin Jarrett, Koray Kavukcuoglu, Karol Gregor, Yann LeCun:
What is the Best Feature Learning Procedure in Hierarchical Recognition Architectures? CoRR abs/1606.01535 (2016) - [i11]Karol Gregor, Danilo Jimenez Rezende, Daan Wierstra:
Variational Intrinsic Control. CoRR abs/1611.07507 (2016) - 2015
- [c10]Mathieu Germain, Karol Gregor, Iain Murray, Hugo Larochelle:
MADE: Masked Autoencoder for Distribution Estimation. ICML 2015: 881-889 - [c9]Tom Schaul, Daniel Horgan, Karol Gregor, David Silver:
Universal Value Function Approximators. ICML 2015: 1312-1320 - [c8]Karol Gregor, Ivo Danihelka, Alex Graves, Danilo Jimenez Rezende, Daan Wierstra:
DRAW: A Recurrent Neural Network For Image Generation. ICML 2015: 1462-1471 - [i10]Mathieu Germain, Karol Gregor, Iain Murray, Hugo Larochelle:
MADE: Masked Autoencoder for Distribution Estimation. CoRR abs/1502.03509 (2015) - [i9]Karol Gregor, Ivo Danihelka, Alex Graves, Daan Wierstra:
DRAW: A Recurrent Neural Network For Image Generation. CoRR abs/1502.04623 (2015) - [i8]Ilya Sutskever, Rafal Józefowicz, Karol Gregor, Danilo Jimenez Rezende, Timothy P. Lillicrap, Oriol Vinyals:
Towards Principled Unsupervised Learning. CoRR abs/1511.06440 (2015) - 2014
- [c7]Karol Gregor, Ivo Danihelka, Andriy Mnih, Charles Blundell, Daan Wierstra:
Deep AutoRegressive Networks. ICML 2014: 1242-1250 - [c6]Andriy Mnih, Karol Gregor:
Neural Variational Inference and Learning in Belief Networks. ICML 2014: 1791-1799 - [i7]Andriy Mnih, Karol Gregor:
Neural Variational Inference and Learning in Belief Networks. CoRR abs/1402.0030 (2014) - 2013
- [i6]Karol Gregor, Andriy Mnih, Daan Wierstra:
Deep AutoRegressive Networks. CoRR abs/1310.8499 (2013) - 2012
- [c5]Arthur Szlam, Karol Gregor, Yann LeCun:
Fast Approximations to Structured Sparse Coding and Applications to Object Classification. ECCV (5) 2012: 200-213 - [c4]Karol Gregor, Dmitri B. Chklovskii:
A lattice filter model of the visual pathway. NIPS 2012: 1718-1726 - [i5]Arthur Szlam, Karol Gregor, Yann LeCun:
Fast approximations to structured sparse coding and applications to object classification. CoRR abs/1202.6384 (2012) - 2011
- [c3]Arthur Szlam, Karol Gregor, Yann LeCun:
Structured sparse coding via lateral inhibition. NIPS 2011: 1116-1124 - [i4]Karol Gregor, Yann LeCun:
Efficient Learning of Sparse Invariant Representations. CoRR abs/1105.5307 (2011) - [i3]Karol Gregor, Yann LeCun:
Learning Representations by Maximizing Compression. CoRR abs/1108.1169 (2011) - 2010
- [c2]Karol Gregor, Yann LeCun:
Learning Fast Approximations of Sparse Coding. ICML 2010: 399-406 - [c1]Koray Kavukcuoglu, Pierre Sermanet, Y-Lan Boureau, Karol Gregor, Michaël Mathieu, Yann LeCun:
Learning Convolutional Feature Hierarchies for Visual Recognition. NIPS 2010: 1090-1098 - [i2]Karol Gregor, Yann LeCun:
Emergence of Complex-Like Cells in a Temporal Product Network with Local Receptive Fields. CoRR abs/1006.0448 (2010)
2000 – 2009
- 2009
- [i1]Karol Gregor, Gregory Griffin:
Behavior and performance of the deep belief networks on image classification. CoRR abs/0912.0717 (2009)
Coauthor Index
aka: Danilo J. Rezende
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last updated on 2023-09-28 03:46 CEST by the dblp team
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