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Generative latent-variable models are emerging as promising tools in robotics and reinforcement learning.
Spatial Broadcast Decoder: A Simple Architecture for Learning Disentangled Representations in VAEs
Nicholas Watters, Loic Matthey, Christopher P Burgess, and Alexander Lerchner · 1901
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Nicholas Watters, Loic Matthey, Matko Bosnjak, Christopher P Burgess, and Alexander Lerchner · 1905
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Receptive Fields and Functional Architecture of Monkey Striate Cortex
D. H. Hubel and T. N. Wiesel · 1968
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Independent Component Analysis
Pierre Comon · 1992
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Foundations of Vision
Brian A. Wandell · 1995
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Emergence of Simple-Cell Receptive Field Properties by Learning a Sparse Code for Natural Images
Bruno A. Olshausen and David J. Field · 1996
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Long Short-Term Memory
Sepp Hochreiter and Jürgen Schmidhuber · 1997
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An Introduction to Variational Methods for Graphical Models
Michael I Jordan, Zoubin Ghahramani, Tommi S Jaakkola, and Lawrence K Saul · 1999
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Predictive Coding in the Visual Cortex: A Functional Interpretation of Some Extra-Classical Receptive-Field Effects
Rajesh P. N. Rao and Dana H. Ballard · 1999
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The Information Bottleneck Method
Naftali Tishby, Fernando C Pereira, and William Bialek · 2000
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The Human Visual Cortex
Kalanit Grill-Spector and Rafael Malach · 2004
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A Theory of Cortical Responses
Karl Friston · 2005
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Contour Detection and Hierarchical Image Segmentation
Pablo Arbelaez, Michael Maire, Charless Fowlkes, and Jitendra Malik · 2010
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Deep Sparse Rectifier Neural Networks
Xavier Glorot, Antoine Bordes, and Yoshua Bengio · 2011
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Auto-Encoding Variational Bayes
Diederik P Kingma and Max Welling · 2014
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Stochastic Backpropagation and Approximate Inference in Deep Generative Models
Danilo Jimenez Rezende, Shakir Mohamed, and Daan Wierstra · 2014
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Efficient Inference in Occlusion-Aware Generative models of Images
Jonathan Huang and Kevin Murphy · 2015
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Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
Sergey Ioffe and Christian Szegedy · 2015
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Adam: A Method for Stochastic Optimization
Diederik P Kingma and Jimmy Ba · 2015
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Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs)
Djork-Arné Clevert, Thomas Unterthiner, and Sepp Hochreiter · 2016
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Attend, Infer, Repeat: Fast Scene Understanding with Generative Models
SM Ali Eslami, Nicolas Heess, Theophane Weber, Yuval Tassa, David Szepesvari, Geoffrey E Hinton, et al · 2016
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Tagger: Deep Unsupervised Perceptual Grouping
Klaus Greff, Antti Rasmus, Mathias Berglund, Tele Hao, Harri Valpola, and Jürgen Schmidhuber · 2016
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Language Modeling with Gated Convolutional Networks
Yann N Dauphin, Angela Fan, Michael Auli, and David Grangier · 2017
ShapeStacks: Learning Vision-Based Physical Intuition for Generalised Object Stacking
Oliver Groth, Fabian B Fuchs, Ingmar Posner, and Andrea Vedaldi · 2018
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World Models
David Ha and Jürgen Schmidhuber · 2018
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Sequential Attend, Infer, Repeat: Generative Modelling of Moving Objects
Adam Kosiorek, Hyunjik Kim, Yee Whye Teh, and Ingmar Posner · 2018
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Image Transformer
Niki Parmar, Ashish Vaswani, Jakob Uszkoreit, Łukasz Kaiser, Noam Shazeer, Alexander Ku, and Dustin Tran · 2018
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Danilo Jimenez Rezende and Fabio Viola · 2018
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Multi-Objects Generation with Amortized Structural Regularization
Kun Xu, Chongxuan Li, Jun Zhu, and Bo Zhang · 2018
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Neural Expectation Maximization
Klaus Greff, Sjoerd van Steenkiste, and Jürgen Schmidhuber · 2017
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GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium
Martin Heusel, Hubert Ramsauer, Thomas Unterthiner, Bernhard Nessler, and Sepp Hochreiter · 2017
Cited alongside, same era.
dSprites: Disentanglement Testing Sprites Dataset
Loic Matthey, Irina Higgins, Demis Hassabis, and Alexander Lerchner · 2017
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Vision-as-Inverse-Graphics: Obtaining a Rich 3D Explanation of a Scene from a Single Image
Lukasz Romaszko, Christopher KI Williams, Pol Moreno, and Pushmeet Kohli · 2017
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A Simple Neural Network Module for Relational Reasoning
Adam Santoro, David Raposo, David G. T. Barrett, Mateusz Malinowski, Razvan Pascanu, Peter W. Battaglia, and Timothy P. Lillicrap · 2017
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Inception-V4, Inception-Resnet and the Impact of Residual Connections on Learning
Christian Szegedy, Sergey Ioffe, Vincent Vanhoucke, and Alexander A Alemi · 2017
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Object Discovery with a Copy-Pasting GAN
Relja Arandjelović and Andrew Zisserman · 2019
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Compositional GAN: Learning Image-Conditional Binary Composition
Samaneh Azadi, Deepak Pathak, Sayna Ebrahimi, and Trevor Darrell · 2019
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Emergence of Object Segmentation in Perturbed Generative Models
Adam Bielski and Paolo Favaro · 2019
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MONet: Unsupervised Scene Decomposition and Representation
Christopher P Burgess, Loic Matthey, Nicholas Watters, Rishabh Kabra, Irina Higgins, Matt Botvinick, and Alexander Lerchner · 2019
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Unsupervised Object Segmentation by Redrawing
Mickaël Chen, Thierry Artières, and Ludovic Denoyer · 2019
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Spatially Invariant Unsupervised Object Detection with Convolutional Neural Networks
Eric Crawford and Joelle Pineau · 2019
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Multi-Object Representation Learning with Iterative Variational Inference
Klaus Greff, Raphaël Lopez Kaufmann, Rishab Kabra, Nick Watters, Chris Burgess, Daniel Zoran, Loic Matthey, Matthew Botvinick, and Alexander Lerchner · 2019
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Shaping Belief States with Generative Environment Models for RL
Karol Gregor, Danilo Jimenez Rezende, Frederic Besse, Yan Wu, Hamza Merzic, and Aaron van den Oord · 2019
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Adam R Kosiorek, Sara Sabour, Yee Whye Teh, and Geoffrey E Hinton · 2019
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Are Disentangled Representations Helpful for Abstract Visual Reasoning?
Sjoerd van Steenkiste, Francesco Locatello, Jurgen Schmidhuber, and Olivier Bachem · 2019
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