A citation-based method for searching scientific literature


List of co-cited articles
639 articles co-cited >1



Times Cited
  Times     Co-cited
Similarity


Using goal-driven deep learning models to understand sensory cortex.
Daniel L K Yamins, James J DiCarlo. Nat Neurosci 2016
296
47

Deep learning.
Yann LeCun, Yoshua Bengio, Geoffrey Hinton. Nature 2015
38

Performance-optimized hierarchical models predict neural responses in higher visual cortex.
Daniel L K Yamins, Ha Hong, Charles F Cadieu, Ethan A Solomon, Darren Seibert, James J DiCarlo. Proc Natl Acad Sci U S A 2014
414
31

Deep supervised, but not unsupervised, models may explain IT cortical representation.
Seyed-Mahdi Khaligh-Razavi, Nikolaus Kriegeskorte. PLoS Comput Biol 2014
309
27


Deep neural networks rival the representation of primate IT cortex for core visual object recognition.
Charles F Cadieu, Ha Hong, Daniel L K Yamins, Nicolas Pinto, Diego Ardila, Ethan A Solomon, Najib J Majaj, James J DiCarlo. PLoS Comput Biol 2014
173
20

Comparison of deep neural networks to spatio-temporal cortical dynamics of human visual object recognition reveals hierarchical correspondence.
Radoslaw Martin Cichy, Aditya Khosla, Dimitrios Pantazis, Antonio Torralba, Aude Oliva. Sci Rep 2016
155
18

Representational similarity analysis - connecting the branches of systems neuroscience.
Nikolaus Kriegeskorte, Marieke Mur, Peter Bandettini. Front Syst Neurosci 2008
16

Large-Scale, High-Resolution Comparison of the Core Visual Object Recognition Behavior of Humans, Monkeys, and State-of-the-Art Deep Artificial Neural Networks.
Rishi Rajalingham, Elias B Issa, Pouya Bashivan, Kohitij Kar, Kailyn Schmidt, James J DiCarlo. J Neurosci 2018
66
24

Toward an Integration of Deep Learning and Neuroscience.
Adam H Marblestone, Greg Wayne, Konrad P Kording. Front Comput Neurosci 2016
140
16

How does the brain solve visual object recognition?
James J DiCarlo, Davide Zoccolan, Nicole C Rust. Neuron 2012
512
14

Neuroscience-Inspired Artificial Intelligence.
Demis Hassabis, Dharshan Kumaran, Christopher Summerfield, Matthew Botvinick. Neuron 2017
154
14

Long short-term memory.
S Hochreiter, J Schmidhuber. Neural Comput 1997
13


Deep Neural Networks as a Computational Model for Human Shape Sensitivity.
Jonas Kubilius, Stefania Bracci, Hans P Op de Beeck. PLoS Comput Biol 2016
73
17

A deep learning framework for neuroscience.
Blake A Richards, Timothy P Lillicrap, Philippe Beaudoin, Yoshua Bengio, Rafal Bogacz, Amelia Christensen, Claudia Clopath, Rui Ponte Costa, Archy de Berker, Surya Ganguli,[...]. Nat Neurosci 2019
73
17

A Task-Optimized Neural Network Replicates Human Auditory Behavior, Predicts Brain Responses, and Reveals a Cortical Processing Hierarchy.
Alexander J E Kell, Daniel L K Yamins, Erica N Shook, Sam V Norman-Haignere, Josh H McDermott. Neuron 2018
64
18

Deep learning in neural networks: an overview.
Jürgen Schmidhuber. Neural Netw 2015
11

Deep Neural Networks as Scientific Models.
Radoslaw M Cichy, Daniel Kaiser. Trends Cogn Sci 2019
39
28

Human-level control through deep reinforcement learning.
Volodymyr Mnih, Koray Kavukcuoglu, David Silver, Andrei A Rusu, Joel Veness, Marc G Bellemare, Alex Graves, Martin Riedmiller, Andreas K Fidjeland, Georg Ostrovski,[...]. Nature 2015
722
10

Evidence that recurrent circuits are critical to the ventral stream's execution of core object recognition behavior.
Kohitij Kar, Jonas Kubilius, Kailyn Schmidt, Elias B Issa, James J DiCarlo. Nat Neurosci 2019
53
18

Hierarchical models of object recognition in cortex.
M Riesenhuber, T Poggio. Nat Neurosci 1999
9

Explicit information for category-orthogonal object properties increases along the ventral stream.
Ha Hong, Daniel L K Yamins, Najib J Majaj, James J DiCarlo. Nat Neurosci 2016
103
9

Normalization as a canonical neural computation.
Matteo Carandini, David J Heeger. Nat Rev Neurosci 2011
751
9

Neural population control via deep image synthesis.
Pouya Bashivan, Kohitij Kar, James J DiCarlo. Science 2019
52
17

Recurrence is required to capture the representational dynamics of the human visual system.
Tim C Kietzmann, Courtney J Spoerer, Lynn K A Sörensen, Radoslaw M Cichy, Olaf Hauk, Nikolaus Kriegeskorte. Proc Natl Acad Sci U S A 2019
38
23



Deep Networks Can Resemble Human Feed-forward Vision in Invariant Object Recognition.
Saeed Reza Kheradpisheh, Masoud Ghodrati, Mohammad Ganjtabesh, Timothée Masquelier. Sci Rep 2016
46
17

Deep Learning: The Good, the Bad, and the Ugly.
Thomas Serre. Annu Rev Vis Sci 2019
24
33

Representational geometry: integrating cognition, computation, and the brain.
Nikolaus Kriegeskorte, Rogier A Kievit. Trends Cogn Sci 2013
268
8

Mastering the game of Go with deep neural networks and tree search.
David Silver, Aja Huang, Chris J Maddison, Arthur Guez, Laurent Sifre, George van den Driessche, Julian Schrittwieser, Ioannis Antonoglou, Veda Panneershelvam, Marc Lanctot,[...]. Nature 2016
824
7

Mastering the game of Go without human knowledge.
David Silver, Julian Schrittwieser, Karen Simonyan, Ioannis Antonoglou, Aja Huang, Arthur Guez, Thomas Hubert, Lucas Baker, Matthew Lai, Adrian Bolton,[...]. Nature 2017
384
7

Towards deep learning with segregated dendrites.
Jordan Guerguiev, Timothy P Lillicrap, Blake A Richards. Elife 2017
74
9

Random synaptic feedback weights support error backpropagation for deep learning.
Timothy P Lillicrap, Daniel Cownden, Douglas B Tweed, Colin J Akerman. Nat Commun 2016
98
7

Matching categorical object representations in inferior temporal cortex of man and monkey.
Nikolaus Kriegeskorte, Marieke Mur, Douglas A Ruff, Roozbeh Kiani, Jerzy Bodurka, Hossein Esteky, Keiji Tanaka, Peter A Bandettini. Neuron 2008
614
7

Untangling invariant object recognition.
James J DiCarlo, David D Cox. Trends Cogn Sci 2007
335
7

Building machines that learn and think like people.
Brenden M Lake, Tomer D Ullman, Joshua B Tenenbaum, Samuel J Gershman. Behav Brain Sci 2017
136
7

Theories of Error Back-Propagation in the Brain.
James C R Whittington, Rafal Bogacz. Trends Cogn Sci 2019
37
18


How does Nature Program Neuron Types?
Alexander Borst. Front Neurosci 2008
206
6



Flexible gating of contextual influences in natural vision.
Ruben Coen-Cagli, Adam Kohn, Odelia Schwartz. Nat Neurosci 2015
62
9

Recurrent Convolutional Neural Networks: A Better Model of Biological Object Recognition.
Courtney J Spoerer, Patrick McClure, Nikolaus Kriegeskorte. Front Psychol 2017
33
18

Natural image statistics and neural representation.
E P Simoncelli, B A Olshausen. Annu Rev Neurosci 2001
918
6

Hierarchical Bayesian inference in the visual cortex.
Tai Sing Lee, David Mumford. J Opt Soc Am A Opt Image Sci Vis 2003
506
6

Context-dependent computation by recurrent dynamics in prefrontal cortex.
Valerio Mante, David Sussillo, Krishna V Shenoy, William T Newsome. Nature 2013
512
6


Deep Neural Networks for Modeling Visual Perceptual Learning.
Li K Wenliang, Aaron R Seitz. J Neurosci 2018
19
31


Co-cited is the co-citation frequency, indicating how many articles cite the article together with the query article. Similarity is the co-citation as percentage of the times cited of the query article or the article in the search results, whichever is the lowest. These numbers are calculated for the last 100 citations when articles are cited more than 100 times.