Fetching the paper…
Reading the bibliography…
Disentangled distributed representations of data are desirable for machine learning, since they are more expressive and can generalize from fewer examples.
Principles of neurodynamics. perceptrons and the theory of brain mechanisms
Rosenblatt, Frank · 1961
Earlier work this paper cites.
A model for visual shape recognition
Milner, Peter M · 1974
Earlier work this paper cites.
Maximum likelihood from incomplete data via the EM algorithm
Dempster, Arthur P., Laird, Nan M., and Rubin, Donald B · 1977
Earlier work this paper cites.
Neural network model for a mechanism of pattern recognition unaffected by shift in position - Neocognitron
Fukushima, K · 1979
Earlier work this paper cites.
The correlation theory of brain function
von der Malsburg, Christoph · 1981
Earlier work this paper cites.
Distributed representations
Hinton, Geoffrey E · 1984
Earlier work this paper cites.
The utility driven dynamic error propagation network
Robinson, A. J. and Fallside, F · 1987
Earlier work this paper cites.
Generalization of backpropagation with application to a recurrent gas market model
Werbos, P. J · 1988
Earlier work this paper cites.
Finding minimum entropy codes
Barlow, Horace B., Kaushal, Tej P., and Mitchison, Graeme J · 1989
Earlier work this paper cites.
Forming sparse representations by local anti-Hebbian learning
Földiak, Peter · 1990
Earlier work this paper cites.
Handwritten digit recognition with a back-propagation network
Le Cun, B. Boser, Denker, John S., Henderson, D., Howard, Richard E., Hubbard, W., and Jackel, Lawrence D · 1990
Earlier work this paper cites.
Learning to generate artificial fovea trajectories for target detection
Schmidhuber, Juergen and Huber, Rudolf · 1991
Cited alongside, same era.
Learning factorial codes by predictability minimization
Schmidhuber, Jürgen · 1992
Cited alongside, same era.
Binding in models of perception and brain function
von der Malsburg, Christoph · 1995
Cited alongside, same era.
Becoming a “Greeble” expert: Exploring mechanisms for face recognition
Gauthier, Isabel and Tarr, Michael J · 1997
Cited alongside, same era.
The temporal correlation hypothesis of visual feature integration: Still alive and well
Gray, Charles M · 1999
Cited alongside, same era.
Hierarchical models of object recognition in cortex
Riesenhuber, Maximilian and Poggio, Tomaso · 1999
Cited alongside, same era.
Learning lateral interactions for feature binding and sensory segmentation from prototypic basis interactions
Weng, Shijie, Steil, Jochen Jakob, and Ritter, Helge · 2006
Later among the works it cites.
Scaling learning algorithms towards AI
Bengio, Yoshua, LeCun, Yann, and others · 2007
Later among the works it cites.
Unsupervised segmentation with dynamical units
Rao, Ravishankar A., Cecchi, Guillermo, Peck, Charles C., and Kozloski, James R · 2008
Later among the works it cites.
Extracting and composing robust features with denoising autoencoders
Vincent, Pascal, Larochelle, Hugo, Bengio, Yoshua, and Manzagol, Pierre-Antoine · 2008
Later among the works it cites.
Information theoretic measures for clusterings comparison: Variants, properties, normalization and correction for chance
Vinh, Nguyen Xuan, Epps, Julien, and Bailey, James · 2010
Later among the works it cites.
SLIC superpixels compared to state-of-the-art superpixel methods
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Solutions to the binding problem: Progress through controversy and convergence
Treisman, Anne · 1999
Cited alongside, same era.
Learning iterative image reconstruction in the Neural Abstraction Pyramid
Behnke, Sven · 2001
Cited alongside, same era.
Generalizable relational binding from coarse-coded distributed representations
O’reilly, Randall C. and Busby, Richard S · 2002
Cited alongside, same era.
Three forms of binding and their neural substrates: Alternatives to temporal synchrony
O’Reilly, Randall C., Busby, Richard S., and Soto, Rodolfo · 2003
Cited alongside, same era.
Representation learning: A review and new perspectives
Bengio, Yoshua, Courville, Aaron, and Vincent, Pierre
Cited in the paper.
Generalized denoising auto-encoders as generative models
Bengio, Yoshua, Yao, Li, Alain, Guillaume, and Vincent, Pascal
Cited in the paper.
Achanta, Radhakrishna, Shaji, Appu, Smith, Kevin, Lucchi, Aurelien, Fua, Pascal, and Susstrunk, Sabine · 2012
Later among the works it cites.
The feature-binding problem is an ill-posed problem
Di Lollo, Vincent · 2012
Later among the works it cites.
Neuronal synchrony in Complex-Valued deep networks
Reichert, David P. and Serre, Thomas · 2013
Later among the works it cites.
Neural machine translation by jointly learning to align and translate
Bahdanau, Dzmitry, Cho, Kyunghyun, and Bengio, Yoshua · 2014
Later among the works it cites.
Recurrent models of visual attention
Mnih, Volodymyr, Heess, Nicolas, Graves, Alex, et al · 2014
Later among the works it cites.