A citation-based method for searching scientific literature


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



Times Cited
  Times     Co-cited
Similarity


Deep learning.
Yann LeCun, Yoshua Bengio, Geoffrey Hinton. Nature 2015
23

A fast learning algorithm for deep belief nets.
Geoffrey E Hinton, Simon Osindero, Yee-Whye Teh. Neural Comput 2006
11

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


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
9


Using goal-driven deep learning models to understand sensory cortex.
Daniel L K Yamins, James J DiCarlo. Nat Neurosci 2016
392
6

A survey on deep learning in medical image analysis.
Geert Litjens, Thijs Kooi, Babak Ehteshami Bejnordi, Arnaud Arindra Adiyoso Setio, Francesco Ciompi, Mohsen Ghafoorian, Jeroen A W M van der Laak, Bram van Ginneken, Clara I Sánchez. Med Image Anal 2017
6

Deep learning in neural networks: an overview.
Jürgen Schmidhuber. Neural Netw 2015
5

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
530
5



A general reinforcement learning algorithm that masters chess, shogi, and Go through self-play.
David Silver, Thomas Hubert, Julian Schrittwieser, Ioannis Antonoglou, Matthew Lai, Arthur Guez, Marc Lanctot, Laurent Sifre, Dharshan Kumaran, Thore Graepel,[...]. Science 2018
171
5


Predicting the sequence specificities of DNA- and RNA-binding proteins by deep learning.
Babak Alipanahi, Andrew Delong, Matthew T Weirauch, Brendan J Frey. Nat Biotechnol 2015
874
4

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
521
4

Dermatologist-level classification of skin cancer with deep neural networks.
Andre Esteva, Brett Kuprel, Roberto A Novoa, Justin Ko, Susan M Swetter, Helen M Blau, Sebastian Thrun. Nature 2017
4

Statistics versus machine learning.
Danilo Bzdok, Naomi Altman, Martin Krzywinski. Nat Methods 2018
244
4

Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks.
Shaoqing Ren, Kaiming He, Ross Girshick, Jian Sun. IEEE Trans Pattern Anal Mach Intell 2017
4





A systematic review shows no performance benefit of machine learning over logistic regression for clinical prediction models.
Evangelia Christodoulou, Jie Ma, Gary S Collins, Ewout W Steyerberg, Jan Y Verbakel, Ben Van Calster. J Clin Epidemiol 2019
424
3

Big Data and Machine Learning in Health Care.
Andrew L Beam, Isaac S Kohane. JAMA 2018
476
3

Neural population control via deep image synthesis.
Pouya Bashivan, Kohitij Kar, James J DiCarlo. Science 2019
85
3

Reducing the dimensionality of data with neural networks.
G E Hinton, R R Salakhutdinov. Science 2006
3


Image reconstruction by domain-transform manifold learning.
Bo Zhu, Jeremiah Z Liu, Stephen F Cauley, Bruce R Rosen, Matthew S Rosen. Nature 2018
370
3

A Deep Learning Model to Predict a Diagnosis of Alzheimer Disease by Using 18F-FDG PET of the Brain.
Yiming Ding, Jae Ho Sohn, Michael G Kawczynski, Hari Trivedi, Roy Harnish, Nathaniel W Jenkins, Dmytro Lituiev, Timothy P Copeland, Mariam S Aboian, Carina Mari Aparici,[...]. Radiology 2019
147
3


Building machines that learn and think like people.
Brenden M Lake, Tomer D Ullman, Joshua B Tenenbaum, Samuel J Gershman. Behav Brain Sci 2017
200
3

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
959
3

Deep supervised, but not unsupervised, models may explain IT cortical representation.
Seyed-Mahdi Khaligh-Razavi, Nikolaus Kriegeskorte. PLoS Comput Biol 2014
396
3

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
160
3

Diagnostic Assessment of Deep Learning Algorithms for Detection of Lymph Node Metastases in Women With Breast Cancer.
Babak Ehteshami Bejnordi, Mitko Veta, Paul Johannes van Diest, Bram van Ginneken, Nico Karssemeijer, Geert Litjens, Jeroen A W M van der Laak, Meyke Hermsen, Quirine F Manson, Maschenka Balkenhol,[...]. JAMA 2017
780
3

Machine learning: Trends, perspectives, and prospects.
M I Jordan, T M Mitchell. Science 2015
688
3

A theory of cerebellar cortex.
D Marr. J Physiol 1969
3

SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation.
Vijay Badrinarayanan, Alex Kendall, Roberto Cipolla. IEEE Trans Pattern Anal Mach Intell 2017
995
3

Mastering Atari, Go, chess and shogi by planning with a learned model.
Julian Schrittwieser, Ioannis Antonoglou, Thomas Hubert, Karen Simonyan, Laurent Sifre, Simon Schmitt, Arthur Guez, Edward Lockhart, Demis Hassabis, Thore Graepel,[...]. Nature 2020
38
7

How does the brain solve visual object recognition?
James J DiCarlo, Davide Zoccolan, Nicole C Rust. Neuron 2012
593
3





Lack of patchy horizontal connectivity in primary visual cortex of a mammal without orientation maps.
Stephen D Van Hooser, J Alexander Heimel, Sooyoung Chung, Sacha B Nelson. J Neurosci 2006
48
4



Action potential initiation and backpropagation in neurons of the mammalian CNS.
G Stuart, N Spruston, B Sakmann, M Häusser. Trends Neurosci 1997
514
2

Prediction of electroencephalographic spectra from neurophysiology.
P A Robinson, C J Rennie, J J Wright, H Bahramali, E Gordon, D L Rowe. Phys Rev E Stat Nonlin Soft Matter Phys 2001
224
2


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.