Most cited papers in Advanced Memory and Neural Computing
What are the most cited papers in Advanced Memory and Neural Computing?
The most cited paper in Advanced Memory and Neural Computing is "The rise of graphene" (Andre K. Geim, Kostya S. Novoselov, 2007), with 39,928 citations. Next come "Extreme learning machine: Theory and applications" (13,359) and "The missing memristor found" (11,715).
Showing 50 of 100 papers. Every paper with more than 1,826 citations is listed.
| # | Paper | ||
|---|---|---|---|
| 1 | The rise of graphene Andre K. Geim, Kostya S. Novoselov · Nature Materials | Mar 2007 | 39,928 |
| 2 | Extreme learning machine: Theory and applications Guang-Bin Huang, Qinyu Zhu, Chee‐Kheong Siew · Neurocomputing | 17 May 2006 | 13,359 |
| 3 | The missing memristor found Dmitri B. Strukov, Gregory S. Snider, Duncan R. Stewart et al. · Nature | 30 Apr 2008 | 11,715 |
| 4 | Memristor-The missing circuit element Leon Ong Chua · IEEE Transactions on Circuit Theory | 1971 | 10,276 |
| 5 | Fine Structure Constant Defines Visual Transparency of Graphene Rahul R. Nair, Peter N. Blake, Alexander N. Grigorenko et al. · Science | 3 Apr 2008 | 9,109 |
| 6 | The self-organizing map Teuvo Kohonen · Proceedings of the IEEE | 1990 | 8,261 |
| 7 | Brain–computer interfaces for communication and control Jonathan R. Wolpaw, Niels Birbaumer, Dennis J. McFarland et al. · Clinical Neurophysiology | Jun 2002 | 7,965 |
| 8 | Coordinate Attention for Efficient Mobile Network Design Qibin Hou, Daquan Zhou, Jiashi Feng | Jun 2021 | 6,257 |
| 9 | Redox‐Based Resistive Switching Memories – Nanoionic Mechanisms, Prospects, and Challenges Rainer M. Waser, Regina Dittmann, G. Staikov et al. · Advanced Materials | 6 Jul 2009 | 5,097 |
| 10 | Simple model of spiking neurons Eugene M. Izhikevich · IEEE Transactions on Neural Networks | Nov 2003 | 4,948 |
| 11 | Nanoionics-based resistive switching memories Rainer M. Waser, Masakazu Aono · Nature Materials | Nov 2007 | 4,903 |
| 12 | Magnetic Domain-Wall Racetrack Memory S. Parkin, Masamitsu Hayashi, Luc Thomas · Science | 10 Apr 2008 | 4,658 |
| 13 | In-Datacenter Performance Analysis of a Tensor Processing Unit Norman Paul Jouppi et al. | 15 Jun 2017 | 4,527 |
| 14 | Efficient Processing of Deep Neural Networks: A Tutorial and Survey Vivienne Sze, Yu‐Hsin Chen, Tien-Ju Yang et al. · Proceedings of the IEEE | 20 Nov 2017 | 4,237 |
| 15 | A million spiking-neuron integrated circuit with a scalable communication network and interface Paul A. Merolla, John V. Arthur, Rodrigo Alvarez-Icaza et al. · Science | 7 Aug 2014 | 4,220 |
| 16 | Nanoscale Memristor Device as Synapse in Neuromorphic Systems Sung Hyun Jo, Ting‐Chang Chang, Idongesit E. Ebong et al. · Nano Letters | Mar 2010 | 4,190 |
| 17 | Spin-Torque Switching with the Giant Spin Hall Effect of Tantalum Luqiao Liu, Chi‐Feng Pai, Yi Li et al. · Science | 3 May 2012 | 4,158 |
| 18 | Real-Time Computing Without Stable States: A New Framework for Neural Computation Based on Perturbations Wolfgang Maass, Thomas Natschläger, Henry Markram · Neural Computation | Nov 2002 | 4,151 |
| 19 | Extreme learning machine: a new learning scheme of feedforward neural networks Guang-Bin Huang, Qin‐Yu Zhu, Chee‐Kheong Siew | 5 Apr 2005 | 4,121 |
| 20 | Loihi: A Neuromorphic Manycore Processor with On-Chip Learning Mike Davies et al. · IEEE Micro | 2018 | 3,962 |
| 21 | Nitrogen-Doped Graphene as Efficient Metal-Free Electrocatalyst for Oxygen Reduction in Fuel Cells Liangti Qu, Yong Liu, Jong‐Beom Baek et al. · ACS Nano | 15 Feb 2010 | 3,962 |
| 22 | Harnessing Nonlinearity: Predicting Chaotic Systems and Saving Energy in Wireless Communication Herbert Jaeger, Harald Haas · Science | Apr 2004 | 3,897 |
| 23 | Memristive devices for computing J. Joshua Yang, Dmitri B. Strukov, Duncan R. Stewart · Nature Nanotechnology | 27 Dec 2012 | 3,885 |
| 24 | Ferroelectric Memories James Floyd Scott, Carlos A. Paz de Araújo · Science | 15 Dec 1989 | 3,867 |
| 25 | Deep learning with convolutional neural networks for EEG decoding and visualization Robin Tibor Schirrmeister, Jost Tobias Springenberg, Lukas D. J. Fiederer et al. · Human Brain Mapping | 7 Aug 2017 | 3,759 |
| 26 | An Energy Budget for Signaling in the Grey Matter of the Brain David Attwell, Simon B. Laughlin · Journal of Cerebral Blood Flow & Metabolism | Oct 2001 | 3,625 |
| 27 | Magnetoelectronics Gary A. Prinz · Science | 27 Nov 1998 | 3,595 |
| 28 | Conductance of a Molecular Junction Mark A. Reed, Chongwu Zhou, C. J. Muller et al. · Science | 10 Oct 1997 | 3,469 |
| 29 | Electrical Conductivity in Doped Polyacetylene C. K. Chiang, C. R. Fincher, Y. W. Park et al. · Physical Review Letters | 24 Oct 1977 | 3,345 |
| 30 | Evolving Neural Networks through Augmenting Topologies Kenneth Owen Stanley, Risto P Miikkulainen · Evolutionary Computation | Jun 2002 | 3,317 |
| 31 | Talking off the top of your head: toward a mental prosthesis utilizing event-related brain potentials Lawrence A. Farwell, Emanuel Donchin · Electroencephalography and Clinical Neurophysiology | Dec 1988 | 3,235 |
| 32 | Eyeriss: An Energy-Efficient Reconfigurable Accelerator for Deep Convolutional Neural Networks Yu-Hsin Chen, Tushar Krishna, Joel Emer et al. · IEEE Journal of Solid-State Circuits | 8 Nov 2016 | 3,230 |
| 33 | Skyrmions on the track ALBERT FERT, Vincent Cros, J. Sampaio · Nature Nanotechnology | Mar 2013 | 3,206 |
| 34 | Information consensus in multivehicle cooperative control Wei Ren, Randal W. Beard, Ella M. Atkins · IEEE Control Systems | Apr 2007 | 3,198 |
| 35 | Training and operation of an integrated neuromorphic network based on metal-oxide memristors M. Prezioso, Farshad Merrikh‐Bayat, Brian D. Hoskins et al. · Nature | May 2015 | 3,024 |
| 36 | Reservoir computing approaches to recurrent neural network training Mantas Lukoševičius, Herbert Jaeger · Computer Science Review | 14 May 2009 | 3,015 |
| 37 | Perpendicular switching of a single ferromagnetic layer induced by in-plane current injection Ioan Mihai Miron, Kévin Garello, Gilles Gaudin et al. · Nature | 29 Jul 2011 | 3,007 |
| 38 | Memristive switching mechanism for metal/oxide/metal nanodevices J. Joshua Yang, Matthew D. Pickett, Xuema Li et al. · Nature Nanotechnology | 15 Jun 2008 | 2,993 |
| 39 | Resistive switching in transition metal oxides Akihito Sawa · Materials Today | 21 May 2008 | 2,957 |
| 40 | Working memory span tasks: A methodological review and user’s guide Andrew R. A. Conway, Michael J. Kane, Michael F. Bunting et al. · Psychonomic Bulletin & Review | Oct 2005 | 2,918 |
| 41 | On the mean accuracy of statistical pattern recognizers Gary W. Hughes · IEEE Transactions on Information Theory | 1968 | 2,877 |
| 42 | Competitive Hebbian learning through spike-timing-dependent synaptic plasticity Sen Song, Kenneth D. Miller, L. F. Abbott · Nature Neuroscience | Sep 2000 | 2,810 |
| 43 | Lattice-Gas Automata for the Navier-Stokes Equation U. Frisch, B. Hasslacher, Yves Pomeau · Physical Review Letters | 7 Apr 1986 | 2,791 |
| 44 | Highly Crystalline Multimetallic Nanoframes with Three-Dimensional Electrocatalytic Surfaces Chen Chen, Yijin Kang, Ziyang Huo et al. · Science | 28 Feb 2014 | 2,777 |
| 45 | Metal–Oxide RRAM H.-S. Philip Wong, Heng-Yuan Lee, Shimeng Yu et al. · Proceedings of the IEEE | 25 May 2012 | 2,746 |
| 46 | Regularized Evolution for Image Classifier Architecture Search Esteban Real, Alok Aggarwal, Yanping Huang et al. · AAAI Publications (The Association for the Advancement of Artificial Intelligence (AAAI)) | 17 Jul 2019 | 2,713 |
| 47 | A review of classification algorithms for EEG-based brain–computer interfaces Fabien Lotte, Marco Congedo, Anne-Isabelle LECUYER et al. · Journal of Neural Engineering | 31 Jan 2007 | 2,685 |
| 48 | Logic Circuits with Carbon Nanotube Transistors Adrian Bachtold, P. Hadley, Takeshi Nakanishi et al. · Science | 9 Nov 2001 | 2,623 |
| 49 | Memristive devices and systems Leon Ong Chua, Sung Mo Kang · Proceedings of the IEEE | 1976 | 2,620 |
| 50 | Which Model to Use for Cortical Spiking Neurons? Eugene M. Izhikevich · IEEE Transactions on Neural Networks | Sep 2004 | 2,613 |
Citations are OpenAlex's own counts, from its 2026-09-23 snapshot, so the ranking can differ from Google Scholar or Web of Science. A paper is listed for a field when OpenAlex files it under one of the field's topics; retracted papers and papers whose citation count cannot be traced to citing works are left out, and a preprint and the article it became are shown once. Release dates are OpenAlex's: where a source gave only a month or a year, that is what is shown. How the lists are chosen.