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A curated list of resources dedicated to bridge between Cognitive Science and Deep Learning
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README.md

README.md

awesome-cognitive-science-and-deep-learning

A curated list of resources dedicated to bridge between coginitive science and deep learning

Table of Contents

Theory

Papers / Thesis

2017:

  1. STDP-Compatible Approximation of Backpropagation in an Energy-Based Model|Yoshua Bengio, Thomas Mesnard, Asja Fischer, Saizheng Zhang, Yuhuai Wu|2017
    Source: http://www.mitpressjournals.org/doi/full/10.1162/NECO_a_00934#.WRFhOiakU_s

  2. Deep Learning with Dynamic Spiking Neurons and Fixed Feedback Weights |Arash Samadi, Timothy P. Lillicrap, Douglas B. Tweed|2017
    Source: http://sci-hub.cc/10.1162/neco_a_00929

  3. Solving Nonlinearly Separable Classifications in a Single-Layer Neural Network|Nolan Conaway, Kenneth J. Kurtz|2017
    Source: http://sci-hub.cc/10.1162/neco_a_00931

  4. Learning the Structural Vocabulary of a Network|Saket Navlakha|2014
    Source: http://www.mitpressjournals.org/doi/pdf/10.1162/NECO_a_00924

  5. Multistability of Delayed Recurrent Neural Networks with Mexican Hat Activation Functions|Peng Liu, Zhigang Zeng, Jun Wang|2017
    Source: http://sci-hub.cc/10.1162/neco_a_00922

  6. Controllability Analysis of the Neural Mass Model with Dynamic Parameters|Xian Liu, Jing Gao, Guan Wang, Zhi-Wang Chen|2017
    Source: http://sci-hub.cc/10.1162/neco_a_00925

  7. Energy Model of Neuron Activation|Yuriy Romanyshyn, Andriy Smerdov, Svitlana Petrytska|2017 Source: http://sci-hub.cc/10.1162/neco_a_00913

  8. Active Inference: A Process Theory|Karl Friston, Thomas FitzGerald, Francesco Rigoli, Philipp Schwartenbeck, Giovanni Pezzulo|2017
    Source: http://www.mitpressjournals.org/doi/pdf/10.1162/NECO_a_00912

  9. A Combinatorial Model for Dentate Gyrus Sparse Coding |William Severa, Ojas Parekh, Conrad D. James, James B. Aimone|2017
    Source: http://sci-hub.cc/10.1162/neco_a_00905

  10. A Network Model of the Emotional Brain|Luiz Pessoa|2017
    Source: http://sci-hub.cc/10.1016/j.tics.2017.03.002

  11. Bayesian Brains without Probabilities|Sanborn et al.|2017
    Source: http://sci-hub.cc/10.1016/j.tics.2016.10.003

  12. Perceptual Decision-Making: Picking the Low-Hanging Fruit?|Floris P. de Lange, Matthias Fritsche|2017
    Source: http://sci-hub.cc/10.1016/j.tics.2017.03.006

  13. Exercising Control Over Memory Consolidation|Edwin M. Robertson, Adam Takacs|2017
    Source: http://twin.sci-hub.cc/9b3a10641014af416f50d91b0db04091/robertson2017.pdf?download=true

  14. Injured Brains and Adaptive Networks: The Benefits and Costs of Hyperconnectivity|Frank G. Hillary, Jordan H. Grafman|2017
    Source: http://sci-hub.cc/10.1016/j.tics.2017.03.003

  15. An Update on Memory Reconsolidation Updating|Jonathan L.C. Lee, Karim Nader, Daniela Schiller|2017

  16. Linking ADHD to the Neural Circuitry of Attention|Adrienne Mueller, David S. Hong, Steven Shepard, Tirin Moore|2017M
    Source: http://sci-hub.cc/10.1016/j.tics.2017.03.009

  17. Emotion Perception from Face, Voice, and Touch: Comparisons and Convergence|Annett Schirmer, Ralph Adolphs|2017
    Source: http://sci-hub.cc/10.1016/j.tics.2017.01.001

  18. The Depressed Brain: An Evolutionary Systems Theory|Paul B. Badcock, Christopher G. Davey, Sarah Whittle, Nicholas B. Allen, Karl J. Friston |2017
    Source: http://sci-hub.cc/10.1016/j.tics.2017.01.005

  19. Gradients of Connectivity in the Cerebral Cortex|Fenna M. Krienen, Chet C. Sherwood|2016
    Source: http://sci-hub.cc/10.1016/j.tics.2016.12.002

  20. How Do We Keep Information ‘Online’?|David Soto|2017

  21. The Distributed Nature of Working Memory|Thomas B. Christophel, P. Christiaan Klink, Bernhard Spitzer, Pieter R. Roelfsema, John-Dylan Haynes|2017
    Source: http://sci-hub.bz/10.1016/j.tics.2016.12.007

  22. F2 Heterogeneous layers stabilize propagation of a multiplexed spike signal in a feedforward network|Dongqi Han, Sungho Hong|2017
    Source: https://bmcneurosci.biomedcentral.com/articles/10.1186/s12868-017-0370-3

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