A citation-based method for searching scientific literature

Olivier J Hénaff, Robbe L T Goris, Eero P Simoncelli. Nat Neurosci 2019
Times Cited: 6







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



Times Cited
  Times     Co-cited
Similarity


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
436
83

How does the brain solve visual object recognition?
James J DiCarlo, Davide Zoccolan, Nicole C Rust. Neuron 2012
523
83

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
66

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
182
66

Hierarchical models of object recognition in cortex.
M Riesenhuber, T Poggio. Nat Neurosci 1999
66

Deep supervised, but not unsupervised, models may explain IT cortical representation.
Seyed-Mahdi Khaligh-Razavi, Nikolaus Kriegeskorte. PLoS Comput Biol 2014
328
66


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
38
50

Neural population control via deep image synthesis.
Pouya Bashivan, Kohitij Kar, James J DiCarlo. Science 2019
57
50

Untangling invariant object recognition.
James J DiCarlo, David D Cox. Trends Cogn Sci 2007
344
50

Deep learning.
Yann LeCun, Yoshua Bengio, Geoffrey Hinton. Nature 2015
50

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
626
50


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
62
50

DeepLabCut: markerless pose estimation of user-defined body parts with deep learning.
Alexander Mathis, Pranav Mamidanna, Kevin M Cury, Taiga Abe, Venkatesh N Murthy, Mackenzie Weygandt Mathis, Matthias Bethge. Nat Neurosci 2018
412
33

Neuroscience-Inspired Artificial Intelligence.
Demis Hassabis, Dharshan Kumaran, Christopher Summerfield, Matthew Botvinick. Neuron 2017
162
33

Long short-term memory.
S Hochreiter, J Schmidhuber. Neural Comput 1997
33

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
42
33

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
164
33

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
759
33

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
406
33

Shape representation in the inferior temporal cortex of monkeys.
N K Logothetis, J Pauls, T Poggio. Curr Biol 1995
535
33


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
33

Using goal-driven deep learning models to understand sensory cortex.
Daniel L K Yamins, James J DiCarlo. Nat Neurosci 2016
314
33

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
37
33

The importance of mixed selectivity in complex cognitive tasks.
Mattia Rigotti, Omri Barak, Melissa R Warden, Xiao-Jing Wang, Nathaniel D Daw, Earl K Miller, Stefano Fusi. Nature 2013
516
33

High-dimensional geometry of population responses in visual cortex.
Carsen Stringer, Marius Pachitariu, Nicholas Steinmetz, Matteo Carandini, Kenneth D Harris. Nature 2019
62
33

Signals in inferotemporal and perirhinal cortex suggest an untangling of visual target information.
Marino Pagan, Luke S Urban, Margot P Wohl, Nicole C Rust. Nat Neurosci 2013
64
33

Flexible timing by temporal scaling of cortical responses.
Jing Wang, Devika Narain, Eghbal A Hosseini, Mehrdad Jazayeri. Nat Neurosci 2018
107
33

A neural network that finds a naturalistic solution for the production of muscle activity.
David Sussillo, Mark M Churchland, Matthew T Kaufman, Krishna V Shenoy. Nat Neurosci 2015
141
33


Context-dependent computation by recurrent dynamics in prefrontal cortex.
Valerio Mante, David Sussillo, Krishna V Shenoy, William T Newsome. Nature 2013
522
33


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
90
33

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
44
33

Backpropagation and the brain.
Timothy P Lillicrap, Adam Santoro, Luke Marris, Colin J Akerman, Geoffrey Hinton. Nat Rev Neurosci 2020
39
33


Comparing machines and humans on a visual categorization test.
François Fleuret, Ting Li, Charles Dubout, Emma K Wampler, Steven Yantis, Donald Geman. Proc Natl Acad Sci U S A 2011
21
16


Spatiotemporal energy models for the perception of motion.
E H Adelson, J R Bergen. J Opt Soc Am A 1985
16

Neural mechanisms for the recognition of biological movements.
Martin A Giese, Tomaso Poggio. Nat Rev Neurosci 2003
419
16

A generative vision model that trains with high data efficiency and breaks text-based CAPTCHAs.
Dileep George, Wolfgang Lehrach, Ken Kansky, Miguel Lázaro-Gredilla, Christopher Laan, Bhaskara Marthi, Xinghua Lou, Zhaoshi Meng, Yi Liu, Huayan Wang,[...]. Science 2017
23
16


Convolutional Oriented Boundaries: From Image Segmentation to High-Level Tasks.
Kevis-Kokitsi Maninis, Jordi Pont-Tuset, Pablo Arbelaez, Luc Van Gool. IEEE Trans Pattern Anal Mach Intell 2018
12
16

Humans, but Not Deep Neural Networks, Often Miss Giant Targets in Scenes.
Miguel P Eckstein, Kathryn Koehler, Lauren E Welbourne, Emre Akbas. Curr Biol 2017
21
16


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
864
16

Evaluating (and Improving) the Correspondence Between Deep Neural Networks and Human Representations.
Joshua C Peterson, Joshua T Abbott, Thomas L Griffiths. Cogn Sci 2018
17
16

Multi-column deep neural network for traffic sign classification.
Dan Cireşan, Ueli Meier, Jonathan Masci, Jürgen Schmidhuber. Neural Netw 2012
80
16


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.