A citation-based method for searching scientific literature

Friedemann Zenke, Surya Ganguli. Neural Comput 2018
Times Cited: 68







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



Times Cited
  Times     Co-cited
Similarity


Artificial brains. A million spiking-neuron integrated circuit with a scalable communication network and interface.
Paul A Merolla, John V Arthur, Rodrigo Alvarez-Icaza, Andrew S Cassidy, Jun Sawada, Filipp Akopyan, Bryan L Jackson, Nabil Imam, Chen Guo, Yutaka Nakamura,[...]. Science 2014
563
30

Deep learning.
Yann LeCun, Yoshua Bengio, Geoffrey Hinton. Nature 2015
29

Training Deep Spiking Neural Networks Using Backpropagation.
Jun Haeng Lee, Tobi Delbruck, Michael Pfeiffer. Front Neurosci 2016
118
29

Supervised Learning Based on Temporal Coding in Spiking Neural Networks.
Hesham Mostafa. IEEE Trans Neural Netw Learn Syst 2018
53
35


The tempotron: a neuron that learns spike timing-based decisions.
Robert Gütig, Haim Sompolinsky. Nat Neurosci 2006
246
23

STDP-based spiking deep convolutional neural networks for object recognition.
Saeed Reza Kheradpisheh, Mohammad Ganjtabesh, Simon J Thorpe, Timothée Masquelier. Neural Netw 2018
89
20

Conversion of Continuous-Valued Deep Networks to Efficient Event-Driven Networks for Image Classification.
Bodo Rueckauer, Iulia-Alexandra Lungu, Yuhuang Hu, Michael Pfeiffer, Shih-Chii Liu. Front Neurosci 2017
85
20

Deep Learning With Spiking Neurons: Opportunities and Challenges.
Michael Pfeiffer, Thomas Pfeil. Front Neurosci 2018
58
24

Random synaptic feedback weights support error backpropagation for deep learning.
Timothy P Lillicrap, Daniel Cownden, Douglas B Tweed, Colin J Akerman. Nat Commun 2016
136
19

Convolutional networks for fast, energy-efficient neuromorphic computing.
Steven K Esser, Paul A Merolla, John V Arthur, Andrew S Cassidy, Rathinakumar Appuswamy, Alexander Andreopoulos, David J Berg, Jeffrey L McKinstry, Timothy Melano, Davis R Barch,[...]. Proc Natl Acad Sci U S A 2016
102
19


Deep learning in spiking neural networks.
Amirhossein Tavanaei, Masoud Ghodrati, Saeed Reza Kheradpisheh, Timothée Masquelier, Anthony Maida. Neural Netw 2019
77
19

Spatio-Temporal Backpropagation for Training High-Performance Spiking Neural Networks.
Yujie Wu, Lei Deng, Guoqi Li, Jun Zhu, Luping Shi. Front Neurosci 2018
64
18

Learning by the dendritic prediction of somatic spiking.
Robert Urbanczik, Walter Senn. Neuron 2014
76
16

Event-Driven Random Back-Propagation: Enabling Neuromorphic Deep Learning Machines.
Emre O Neftci, Charles Augustine, Somnath Paul, Georgios Detorakis. Front Neurosci 2017
48
22

Simple model of spiking neurons.
E M Izhikevich. IEEE Trans Neural Netw 2003
16



Deep learning in neural networks: an overview.
Jürgen Schmidhuber. Neural Netw 2015
14

Optimal spike-timing-dependent plasticity for precise action potential firing in supervised learning.
Jean-Pascal Pfister, Taro Toyoizumi, David Barber, Wulfram Gerstner. Neural Comput 2006
115
14

Supervised learning in spiking neural networks with FORCE training.
Wilten Nicola, Claudia Clopath. Nat Commun 2017
53
18


Towards deep learning with segregated dendrites.
Jordan Guerguiev, Timothy P Lillicrap, Blake A Richards. Elife 2017
108
13


Learning real-world stimuli in a neural network with spike-driven synaptic dynamics.
Joseph M Brader, Walter Senn, Stefano Fusi. Neural Comput 2007
114
13

A solution to the learning dilemma for recurrent networks of spiking neurons.
Guillaume Bellec, Franz Scherr, Anand Subramoney, Elias Hajek, Darjan Salaj, Robert Legenstein, Wolfgang Maass. Nat Commun 2020
40
22


A reconfigurable on-line learning spiking neuromorphic processor comprising 256 neurons and 128K synapses.
Ning Qiao, Hesham Mostafa, Federico Corradi, Marc Osswald, Fabio Stefanini, Dora Sumislawska, Giacomo Indiveri. Front Neurosci 2015
120
11

Unsupervised learning of visual features through spike timing dependent plasticity.
Timothée Masquelier, Simon J Thorpe. PLoS Comput Biol 2007
159
11

Neuroscience-Inspired Artificial Intelligence.
Demis Hassabis, Dharshan Kumaran, Christopher Summerfield, Matthew Botvinick. Neuron 2017
240
11

Span: spike pattern association neuron for learning spatio-temporal spike patterns.
Ammar Mohemmed, Stefan Schliebs, Satoshi Matsuda, Nikola Kasabov. Int J Neural Syst 2012
72
11

Supervised learning in multilayer spiking neural networks.
Ioana Sporea, André Grüning. Neural Comput 2013
35
22

Learning precisely timed spikes.
Raoul-Martin Memmesheimer, Ran Rubin, Bence P Olveczky, Haim Sompolinsky. Neuron 2014
53
15

Going Deeper in Spiking Neural Networks: VGG and Residual Architectures.
Abhronil Sengupta, Yuting Ye, Robert Wang, Chiao Liu, Kaushik Roy. Front Neurosci 2019
65
12

Control of synaptic plasticity in deep cortical networks.
Pieter R Roelfsema, Anthony Holtmaat. Nat Rev Neurosci 2018
76
10

Connectivity reflects coding: a model of voltage-based STDP with homeostasis.
Claudia Clopath, Lars Büsing, Eleni Vasilaki, Wulfram Gerstner. Nat Neurosci 2010
299
10

Spiking neural networks.
Samanwoy Ghosh-Dastidar, Hojjat Adeli. Int J Neural Syst 2009
207
10



Real-time classification and sensor fusion with a spiking deep belief network.
Peter O'Connor, Daniel Neil, Shih-Chii Liu, Tobi Delbruck, Michael Pfeiffer. Front Neurosci 2013
93
10

Converting Static Image Datasets to Spiking Neuromorphic Datasets Using Saccades.
Garrick Orchard, Ajinkya Jayawant, Gregory K Cohen, Nitish Thakor. Front Neurosci 2015
62
11

Which model to use for cortical spiking neurons?
Eugene M Izhikevich. IEEE Trans Neural Netw 2004
539
10

Spike-based strategies for rapid processing.
S Thorpe, A Delorme, R Van Rullen. Neural Netw 2001
212
10

Context-dependent computation by recurrent dynamics in prefrontal cortex.
Valerio Mante, David Sussillo, Krishna V Shenoy, William T Newsome. Nature 2013
621
10

Stochastic variational learning in recurrent spiking networks.
Danilo Jimenez Rezende, Wulfram Gerstner. Front Comput Neurosci 2014
31
22

Towards spike-based machine intelligence with neuromorphic computing.
Kaushik Roy, Akhilesh Jaiswal, Priyadarshini Panda. Nature 2019
94
10

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
165
10

Equilibrium Propagation: Bridging the Gap between Energy-Based Models and Backpropagation.
Benjamin Scellier, Yoshua Bengio. Front Comput Neurosci 2017
57
10



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.