Mark D. McDonnell - Google Scholar Citations

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Citations	3482	2176
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Derek AbbottProfessor of Electrical & Electronic Engineering, University of Adelaide, AustraliaVerified email at adelaide.edu.au
nigel g stocksprofessor, university of warwickVerified email at eng.warwick.ac.uk
Charles E. M. PearceElder Chair of Mathematics, University of AdelaideVerified email at adelaide.edu.au
Lawrence M WardProfessor of Psychology, University of British ColumbiaVerified email at psych.ubc.ca
Migel D TisseraPhDVerified email at compression.ai
Victor StamatescuVerified email at adelaide.edu.au
Sebastien WongConsilium Technology, University of South AustraliaVerified email at consilium.technology
Tony VladusichResearch Fellow at Institute for Telecommunications Research, University of South AustraliaVerified email at unisa.edu.au
Dr. (Demi) Xiao GaoMcKenzie Fellow, Biomedical Engineering, The University of MelbourneVerified email at unimelb.edu.au
David GraydenDept. of Biomedical Engineering, University of MelbourneVerified email at unimelb.edu.au
André van SchaikDirector, International Centre for Neuromorphic Systems, Western Sydney UniversityVerified email at westernsydney.edu.au
Nicolangelo IannellaSenior Research fellow, The University of Oslo, Faculty of Mathematics and Natural SciencesVerified email at ibv.uio.no
Hugh PossinghamThe Chief Scientist, The Nature ConservancyVerified email at tnc.org
Weisi GuoChair of Human Machine Intelligence - Cranfield University; Visiting Fellow - Alan Turing InstituteVerified email at cranfield.ac.uk
Siyi WangLecturer of Electrical and Electronic Engineering, The University of LiverpoolVerified email at liverpool.ac.uk
Bahar MoezziUniversity of South AustrliaVerified email at mymail.unisa.edu.au
Lachlan J GunnDepartment of Computer Science, Aalto UniversityVerified email at aalto.fi
Matthew BerrymanIT Architect, University of WollongongVerified email at uow.edu.au
Jonathan TapsonProfessor, School of Computing, Engineering and Mathematics, Western Sydney UniversityVerified email at westernsydney.edu.au
Fabing DUANProfessor of Institute of Complexity Science, Qingdao University (Email: fabing.duan@gmail.com)Verified email at qdu.edu.cn

Mark D. McDonnell

Computational Learning Systems Laboratory, University of South Australia

Verified email at unisa.edu.au - Homepage

machine learning computer vision computational neuroscience stochastic resonance


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What is stochastic resonance? Definitions, misconceptions, debates, and its relevance to biology MD McDonnell, D Abbott PLoS Comput Biol 5 (5), e1000348, 2009	590	2009
The benefits of noise in neural systems: bridging theory and experiment MD McDonnell, LM Ward Nature Reviews Neuroscience 12 (7), 415-425, 2011	471	2011
Understanding data augmentation for classification: when to warp? SC Wong, A Gatt, V Stamatescu, MD McDonnell 2016 international conference on digital image computing: techniques and …, 2016	361	2016
Mathematical methods for spatially cohesive reserve design MD McDonnell, HP Possingham, IR Ball, EA Cousins Environmental Modeling & Assessment 7 (2), 107-114, 2002	301	2002
Stochastic resonance MD McDonnell, NG Stocks, CEM Pearce, D Abbott Stochastic Resonance, by Mark D. McDonnell, Nigel G. Stocks, Charles EM …, 2008	275	2008
Stochastic resonance: from suprathreshold stochastic resonance to stochastic signal quantization MD McDonnell, NG Stocks, CEM Pearce, D Abbott Cambridge University Press, 2008	275*	2008
Optimal information transmission in nonlinear arrays through suprathreshold stochastic resonance MD McDonnell, NG Stocks, CEM Pearce, D Abbott Physics Letters A 352 (3), 183-189, 2006	82	2006
Methods for generating complex networks with selected structural properties for simulations: a review and tutorial for neuroscientists BJ Prettejohn, MJ Berryman, MD McDonnell Frontiers in Computational Neuroscience 5, 2011	80	2011
An analysis of noise enhanced information transmission in an array of comparators MD McDonnell, D Abbott, CEM Pearce Microelectronics Journal 33 (12), 1079-1089, 2002	78	2002
Deep extreme learning machines: supervised autoencoding architecture for classification MD Tissera, MD McDonnell Neurocomputing 174, 42-49, 2016	70	2016
Enhanced image classification with a fast-learning shallow convolutional neural network MD McDonnell, T Vladusich 2015 International Joint Conference on Neural Networks (IJCNN), 1-7, 2015	64	2015
Fast, simple and accurate handwritten digit classification by training shallow neural network classifiers with the ‘extreme learning machine’algorithm MD McDonnell, MD Tissera, T Vladusich, A van Schaik, J Tapson PloS one 10 (8), e0134254, 2015	61	2015
A characterization of suprathreshold stochastic resonance in an array of comparators by correlation coefficient MD Mcdonnell, D Abbott, CEM Pearce Fluctuation and noise letters 2 (03), L205-L220, 2002	61	2002
Maximally informative stimuli and tuning curves for sigmoidal rate-coding neurons and populations MD McDonnell, NG Stocks Physical review letters 101 (5), 058103, 2008	57	2008
Optimal stimulus and noise distributions for information transmission via suprathreshold stochastic resonance MD McDonnell, NG Stocks, D Abbott Physical Review E 75 (6), 061105, 2007	52	2007
Neural population coding is optimized by discrete tuning curves AP Nikitin, NG Stocks, RP Morse, MD McDonnell Physical review letters 103 (13), 138101, 2009	46	2009
Is electrical noise useful?[point of view] MD McDonnell Proceedings of the IEEE 99 (2), 242-246, 2011	37	2011
Quantization in the presence of large amplitude threshold noise MD McDonnell, NG STOCKS, CEM PEARCE, D ABBOTT Fluctuation and Noise Letters 5 (03), L457-L468, 2005	32	2005
Training wide residual networks for deployment using a single bit for each weight MD McDonnell arXiv preprint arXiv:1802.08530, 2018	31	2018
Stochastic pooling networks MD McDonnell, PO Amblard, NG Stocks Journal of Statistical Mechanics: Theory and Experiment 2009 (01), P01012, 2009	31	2009

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