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Learning modular structures which reflect the dynamics of the environment can lead to better generalization and robustness to changes which only affect a few of the underlying causes.
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beta-vae: Learning basic visual concepts with a constrained variational framework
Irina Higgins, Loic Matthey, Arka Pal, Christopher Burgess, Xavier Glorot, Matthew Botvinick, Shakir Mohamed, and Alexander Lerchner · 2016
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Variable computation in recurrent neural networks
Yacine Jernite, Edouard Grave, Armand Joulin, and Tomas Mikolov · 2016
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Zoneout: Regularizing rnns by randomly preserving hidden activations
David Krueger, Tegan Maharaj, János Kramár, Mohammad Pezeshki, Nicolas Ballas, Nan Rosemary Ke, Anirudh Goyal, Yoshua Bengio, Aaron Courville, and Chris Pal · 2016
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Phased lstm: Accelerating recurrent network training for long or event-based sequences
Daniel Neil, Michael Pfeiffer, and Shih-Chii Liu · 2016
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Yoshua Bengio · 2017
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Geometric deep learning: going beyond euclidean data
Michael M Bronstein, Joan Bruna, Yann LeCun, Arthur Szlam, and Pierre Vandergheynst · 2017
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David Ha and Jürgen Schmidhuber · 2018
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Danijar Hafner, Timothy Lillicrap, Ian Fischer, Ruben Villegas, David Ha, Honglak Lee, and James Davidson · 2018
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Matrix capsules with em routing
Geoffrey E Hinton, Sara Sabour, and Nicholas Frosst · 2018
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Sparse attentive backtracking: Temporal credit assignment through reminding
Nan Rosemary Ke, Anirudh Goyal, Olexa Bilaniuk, Jonathan Binas, Michael C Mozer, Chris Pal, and Yoshua Bengio · 2018
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Thomas Kipf, Ethan Fetaya, Kuan-Chieh Wang, Max Welling, and Richard Zemel · 2018
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Louis Kirsch, Julius Kunze, and David Barber · 2018
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Wouter Kool and Matthew Botvinick · 2018
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Pytorch implementations of reinforcement learning algorithms
Ilya Kostrikov · 2018
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Independently recurrent neural network (indrnn): Building a longer and deeper rnn
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Giambattista Parascandolo, Niki Kilbertus, Mateo Rojas-Carulla, and Bernhard Schölkopf · 2018
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Adam Santoro, Ryan Faulkner, David Raposo, Jack W. Rae, Mike Chrzanowski, Theophane Weber, Daan Wierstra, Oriol Vinyals, Razvan Pascanu, and Timothy P. Lillicrap · 2018
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Jürgen Schmidhuber · 2018
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Relational forward models for multi-agent learning
Andrea Tacchetti, H Francis Song, Pedro AM Mediano, Vinicius Zambaldi, Neil C Rabinowitz, Thore Graepel, Matthew Botvinick, and Peter W Battaglia · 2018
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A meta-transfer objective for learning to disentangle causal mechanisms
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Learning powerful policies by using consistent dynamics model
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