A citation-based method for searching scientific literature

M Riesenhuber, T Poggio. Nat Neurosci 1999
Times Cited: 1067







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



Times Cited
  Times     Co-cited
Similarity


How does the brain solve visual object recognition?
James J DiCarlo, Davide Zoccolan, Nicole C Rust. Neuron 2012
512
19

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
18




A feedforward architecture accounts for rapid categorization.
Thomas Serre, Aude Oliva, Tomaso Poggio. Proc Natl Acad Sci U S A 2007
405
13


Deep supervised, but not unsupervised, models may explain IT cortical representation.
Seyed-Mahdi Khaligh-Razavi, Nikolaus Kriegeskorte. PLoS Comput Biol 2014
309
12

Robust object recognition with cortex-like mechanisms.
Thomas Serre, Lior Wolf, Stanley Bileschi, Maximilian Riesenhuber, Tomaso Poggio. IEEE Trans Pattern Anal Mach Intell 2007
302
12

Deep learning.
Yann LeCun, Yoshua Bengio, Geoffrey Hinton. Nature 2015
11


Using goal-driven deep learning models to understand sensory cortex.
Daniel L K Yamins, James J DiCarlo. Nat Neurosci 2016
296
9

Speed of processing in the human visual system.
S Thorpe, D Fize, C Marlot. Nature 1996
9


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
13

The Psychophysics Toolbox.
D H Brainard. Spat Vis 1997
9

A feature-integration theory of attention.
A M Treisman, G Gelade. Cogn Psychol 1980
9

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
16


Untangling invariant object recognition.
James J DiCarlo, David D Cox. Trends Cogn Sci 2007
335
8


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
15

A functional and perceptual signature of the second visual area in primates.
Jeremy Freeman, Corey M Ziemba, David J Heeger, Eero P Simoncelli, J Anthony Movshon. Nat Neurosci 2013
128
7

Coding of border ownership in monkey visual cortex.
H Zhou, H S Friedman, R von der Heydt. J Neurosci 2000
380
7


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
9

Recurrent computations for visual pattern completion.
Hanlin Tang, Martin Schrimpf, William Lotter, Charlotte Moerman, Ana Paredes, Josue Ortega Caro, Walter Hardesty, David Cox, Gabriel Kreiman. Proc Natl Acad Sci U S A 2018
35
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
7

The neural basis of decision making.
Joshua I Gold, Michael N Shadlen. Annu Rev Neurosci 2007
7

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
7

Neural population control via deep image synthesis.
Pouya Bashivan, Kohitij Kar, James J DiCarlo. Science 2019
52
13



Canonical microcircuits for predictive coding.
Andre M Bastos, W Martin Usrey, Rick A Adams, George R Mangun, Pascal Fries, Karl J Friston. Neuron 2012
830
7

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
18


A model of V4 shape selectivity and invariance.
Charles Cadieu, Minjoon Kouh, Anitha Pasupathy, Charles E Connor, Maximilian Riesenhuber, Tomaso Poggio. J Neurophysiol 2007
108
6


Neuroscience-Inspired Artificial Intelligence.
Demis Hassabis, Dharshan Kumaran, Christopher Summerfield, Matthew Botvinick. Neuron 2017
154
6

Inferotemporal cortex and object vision.
K Tanaka. Annu Rev Neurosci 1996
821
6

Neural mechanisms of selective visual attention.
R Desimone, J Duncan. Annu Rev Neurosci 1995
6

Metamers of the ventral stream.
Jeremy Freeman, Eero P Simoncelli. Nat Neurosci 2011
247
6

Deep Learning: The Good, the Bad, and the Ugly.
Thomas Serre. Annu Rev Vis Sci 2019
24
25

Representational similarity analysis - connecting the branches of systems neuroscience.
Nikolaus Kriegeskorte, Marieke Mur, Peter Bandettini. Front Syst Neurosci 2008
5

Do we know what the early visual system does?
Matteo Carandini, Jonathan B Demb, Valerio Mante, David J Tolhurst, Yang Dan, Bruno A Olshausen, Jack L Gallant, Nicole C Rust. J Neurosci 2005
272
5


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
5

Categorical representation of visual stimuli in the primate prefrontal cortex.
D J Freedman, M Riesenhuber, T Poggio, E K Miller. Science 2001
626
5




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.