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Robust perception relies on both bottom-up and top-down signals.
The order of visual processing: “top-down,” “bottom-up,” or “middle-out”
Kinchla, R. A. and Wolfe, J. M · 1979
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An interactive activation model of context effects in letter perception: I. an account of basic findings
McClelland, J. L. and Rumelhart, D. E · 1981
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Distributed Hierarchical Processing in the Primate Cerebral Cortex
Felleman, D. J. and Van Essen, D. C · 1991
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The helmholtz machine
Dayan, P., Hinton, G. E., Neal, R. M., and Zemel, R. S · 1995
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In the theatre of consciousness. global workspace theory, a rigorous scientific theory of consciousness
Baars, B. J · 1997
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Long short-term memory
Hochreiter, S. and Schmidhuber, J · 1997
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Reciprocal connectivity in visual cortex: evidence from fmri
Nielsen, M. L., Tanabe, H., Imaruoka, T., Sekiyama, K., Tashiro, T., and Miyauchi, S · 1999
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On discriminative vs. generative classifiers: A comparison of logistic regression and naive bayes
Ng, A. Y. and Jordan, M. I · 2002
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Motion illusions as optimal percepts
Weiss, Y., Simoncelli, E. P., and Adelson, E. H · 2002
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Object Perception as Bayesian Inference
Kersten, D., Mamassian, P., and Yuille, A · 2004
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A fast learning algorithm for deep belief nets
Hinton, G. E., Osindero, S., and Teh, Y · 2006
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Greedy layer-wise training of deep networks
Bengio, Y., Lamblin, P., Popovici, D., and Larochelle, H · 2007
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Classification using discriminative restricted boltzmann machines
Larochelle, H. and Bengio, Y · 2008
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Deep boltzmann machines
Salakhutdinov, R. and Hinton, G · 2009
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Mechanisms of top-down attention
Baluch, F. and Itti, L · 2011
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Top-down influences on visual processing
Gilbert, C. D · 2013
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What is bottom-up and what is top-down in predictive coding?
Rauss, K. and Pourtois, G · 2013
Cited alongside, same era.
Modulating early visual processing by language
de Vries, H., Strub, F., Mary, J., Larochelle, H., Pietquin, O., and Courville, A. C · 2017
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What is consciousness, and could machines have it?
Dehaene, S., Lau, H., and Kouider, S · 2017
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Distinct top-down and bottom-up brain connectivity during visual perception and imagery
Dijkstra, N., Zeidman, P., Ondobaka, S., and Friston, K · 2017
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Proximal policy optimization algorithms
Schulman, J., Wolski, F., Dhariwal, P., Radford, A., and Klimov, O · 2017
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Attention is all you need
Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N., Kaiser, Ł., and Polosukhin, I · 2017
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Kingma, D. and Ba, J · 2014
Cited alongside, same era.
Visual Areas Exert Feedforward and Feedback Influences through Distinct Frequency Channels
Bastos, A. M., Vezoli, J., Bosman, C. A., Schoffelen, J.-M., Oostenveld, R., Dowdall, J. R., De Weerd, P., Kennedy, H., and Fries, P · 2015
Cited alongside, same era.
A Top-Down Cortical Circuit for Accurate Sensory Perception
Manita, S., Suzuki, T., Homma, C., Matsumoto, T., Odagawa, M., Yamada, K., Ota, K., Matsubara, C., Inutsuka, A., Sato, M., Ohkura, M., Yamanaka, A., Yanagawa, Y., Nakai, J., Hayashi, Y., Larkum, M. E., and Murayama, M · 2015
Cited alongside, same era.
About connections
Rockland, K. S · 2015
Cited alongside, same era.
Hierarchical multiscale recurrent neural networks
Chung, J., Ahn, S., and Bengio, Y · 2016
Cited alongside, same era.
Denton, E. and Fergus, R · 2018
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Pytorch implementations of reinforcement learning algorithms
Kostrikov, I · 2018
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Relational recurrent neural networks
Santoro, A., Faulkner, R., Raposo, D., Rae, J. W., Chrzanowski, M., Weber, T., Wierstra, D., Vinyals, O., Pascanu, R., and Lillicrap, T. P · 2018
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Relational neural expectation maximization: Unsupervised discovery of objects and their interactions
Van Steenkiste, S., Chang, M., Greff, K., and Schmidhuber, J · 2018
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Recurrent independent mechanisms
Goyal, A., Lamb, A., Hoffmann, J., Sodhani, S., Levine, S., Bengio, Y., and Schölkopf, B · 2019
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Convolutional bipartite attractor networks, 2019
Iuzzolino, M., Singer, Y., and Mozer, M. C · 2019
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