A citation-based method for searching scientific literature


List of co-cited articles
574 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
323
43

Deep learning.
Yann LeCun, Yoshua Bengio, Geoffrey Hinton. Nature 2015
35

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
444
32

Deep supervised, but not unsupervised, models may explain IT cortical representation.
Seyed-Mahdi Khaligh-Razavi, Nikolaus Kriegeskorte. PLoS Comput Biol 2014
335
28

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
185
23


Representational similarity analysis - connecting the branches of systems neuroscience.
Nikolaus Kriegeskorte, Marieke Mur, Peter Bandettini. Front Syst Neurosci 2008
18

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
169
17

Toward an Integration of Deep Learning and Neuroscience.
Adam H Marblestone, Greg Wayne, Konrad P Kording. Front Comput Neurosci 2016
143
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
73
21

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
99
15

How does the brain solve visual object recognition?
James J DiCarlo, Davide Zoccolan, Nicole C Rust. Neuron 2012
531
14

Neuroscience-Inspired Artificial Intelligence.
Demis Hassabis, Dharshan Kumaran, Christopher Summerfield, Matthew Botvinick. Neuron 2017
167
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
76
17

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
66
18

Deep Neural Networks as Scientific Models.
Radoslaw M Cichy, Daniel Kaiser. Trends Cogn Sci 2019
46
26

Representational geometry: integrating cognition, computation, and the brain.
Nikolaus Kriegeskorte, Rogier A Kievit. Trends Cogn Sci 2013
286
12

Long short-term memory.
S Hochreiter, J Schmidhuber. Neural Comput 1997
10

Deep learning in neural networks: an overview.
Jürgen Schmidhuber. Neural Netw 2015
10

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
75
13

Deep Learning: The Good, the Bad, and the Ugly.
Thomas Serre. Annu Rev Vis Sci 2019
29
34


Neural population control via deep image synthesis.
Pouya Bashivan, Kohitij Kar, James J DiCarlo. Science 2019
60
15

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
111
9

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

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
50
18

Normalization as a canonical neural computation.
Matteo Carandini, David J Heeger. Nat Rev Neurosci 2011
775
8

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
773
8


Distinct contributions of functional and deep neural network features to representational similarity of scenes in human brain and behavior.
Iris Ia Groen, Michelle R Greene, Christopher Baldassano, Li Fei-Fei, Diane M Beck, Chris I Baker. Elife 2018
42
19

Untangling invariant object recognition.
James J DiCarlo, David D Cox. Trends Cogn Sci 2007
350
7



Deep Convolutional Neural Networks Outperform Feature-Based But Not Categorical Models in Explaining Object Similarity Judgments.
Kamila M Jozwik, Nikolaus Kriegeskorte, Katherine R Storrs, Marieke Mur. Front Psychol 2017
31
22

Building machines that learn and think like people.
Brenden M Lake, Tomer D Ullman, Joshua B Tenenbaum, Samuel J Gershman. Behav Brain Sci 2017
151
7

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

Theories of Error Back-Propagation in the Brain.
James C R Whittington, Rafal Bogacz. Trends Cogn Sci 2019
43
16

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
630
7

Random synaptic feedback weights support error backpropagation for deep learning.
Timothy P Lillicrap, Daniel Cownden, Douglas B Tweed, Colin J Akerman. Nat Commun 2016
107
7

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

Recurrent Convolutional Neural Networks: A Better Model of Biological Object Recognition.
Courtney J Spoerer, Patrick McClure, Nikolaus Kriegeskorte. Front Psychol 2017
38
15


Deep convolutional networks do not classify based on global object shape.
Nicholas Baker, Hongjing Lu, Gennady Erlikhman, Philip J Kellman. PLoS Comput Biol 2018
31
19

Deep convolutional models improve predictions of macaque V1 responses to natural images.
Santiago A Cadena, George H Denfield, Edgar Y Walker, Leon A Gatys, Andreas S Tolias, Matthias Bethge, Alexander S Ecker. PLoS Comput Biol 2019
39
15

Seeing it all: Convolutional network layers map the function of the human visual system.
Michael Eickenberg, Alexandre Gramfort, Gaël Varoquaux, Bertrand Thirion. Neuroimage 2017
64
9

High-dimensional geometry of population responses in visual cortex.
Carsen Stringer, Marius Pachitariu, Nicholas Steinmetz, Matteo Carandini, Kenneth D Harris. Nature 2019
70
8

Evolving Images for Visual Neurons Using a Deep Generative Network Reveals Coding Principles and Neuronal Preferences.
Carlos R Ponce, Will Xiao, Peter F Schade, Till S Hartmann, Gabriel Kreiman, Margaret S Livingstone. Cell 2019
43
13

Towards deep learning with segregated dendrites.
Jordan Guerguiev, Timothy P Lillicrap, Blake A Richards. Elife 2017
81
7

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
884
6

Identifying natural images from human brain activity.
Kendrick N Kay, Thomas Naselaris, Ryan J Prenger, Jack L Gallant. Nature 2008
521
6


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.