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Mark D. McDonnell

Observed names: M D McDonnell, M. D. McDonnell, M. McDonnell, M.D. McDonnell, MARK D. MCDONNELL, Mark D McDonnell, Mark D. Mcdonnell, Mark D. Mcdonnell*a, Mark McDonnell, Mark D. McDonnell, McDonnell, Mark D.
Observed institutions: University of British Columbia, Flinders University, University of South Australia, Chemnitz University of Technology, Adelaide University, The University of Adelaide
ORCID: 0000-0002-7009-3869
Observed ORCID: 0000-0002-7009-3869
OpenAlex ID: A5000677611
Stochastic Resonance: From Suprathreshold Stochastic Resonance to Stochastic Signal Quantization
2008 · Mark D. McDonnell, Nigel G. Stocks, et al. · Cambridge University Press eBooks · 2,473
Understanding Data Augmentation for Classification: When to Warp?
2016 · Sebastien C. Wong, Adam Gatt, et al. · International Conference on Digital Image Computing: Techniques and Applications (DICTA) · 1,049
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What Is Stochastic Resonance? Definitions, Misconceptions, Debates, and Its Relevance to Biology
2009 · Mark D. McDonnell, Derek Abbott · PLoS Computational Biology · 809
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The benefits of noise in neural systems: bridging theory and experiment
2011 · Mark D. McDonnell, Lawrence M. Ward · Nature reviews. Neuroscience · 795
Mathematical Methods for Spatially Cohesive Reserve Design
2002 · Mark D. McDonnell, Hugh P. Possingham, et al. · Environmental Modeling & Assessment · 255
Deep extreme learning machines: supervised autoencoding architecture for classification
2015 · Migel D. Tissera, Mark D. McDonnell · Neurocomputing · 127
25th Annual Computational Neuroscience Meeting: CNS-2016
2016 · the EyeWirers, Tatyana O. Sharpee, et al. · BMC Neuroscience · 110
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Acoustic Scene Classification Using Deep Residual Networks with Late Fusion of Separated High and Low Frequency Paths
2020 · Mark D. McDonnell, Wei Gao · IEEE International Conference on Acoustics Speech and Signal Processing · 100
RanPAC: Random Projections and Pre-trained Models for Continual Learning
2023 · Mark D. McDonnell, Dong Gong, et al. · neural information processing systems · 92
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Enhanced image classification with a fast-learning shallow convolutional neural network
2015 · Mark D. McDonnell, Tony Vladusich · International Joint Conference on Neural Networks (IJCNN) · 91
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Fast, Simple and Accurate Handwritten Digit Classification by Training Shallow Neural Network Classifiers with the ‘Extreme Learning Machine’ Algorithm
2015 · Mark D. McDonnell, Migel D. Tissera, et al. · PLoS ONE · 89
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Methods for Generating Complex Networks with Selected Structural Properties for Simulations: A Review and Tutorial for Neuroscientists
2011 · Brenton J. Prettejohn, Matthew J. Berryman, et al. · Frontiers in Computational Neuroscience · 85
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Optimal information transmission in nonlinear arrays through suprathreshold stochastic resonance
2005 · Mark D. McDonnell, Nigel G. Stocks, et al. · Physics Letters A · 78
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An analysis of noise enhanced information transmission in an array of comparators
2002 · Mark D. McDonnell, Derek Abbott, et al. · Microelectronics Journal · 68
Combining machine learning and conventional statistical approaches for risk factor discovery in a large cohort study
2021 · Iqbal Madakkatel, Ang Zhou, et al. · Scientific Reports · 66
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The Application of Deep Convolutional Neural Networks to Brain Cancer Images: A Survey
2020 · Amin Zadeh Shirazi, Eric Fornaciari, et al. · Journal of Personalized Medicine · 66
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Maximally Informative Stimuli and Tuning Curves for Sigmoidal Rate-Coding Neurons and Populations
2008 · Mark D. McDonnell, Nigel G. Stocks · Physical Review Letters · 65
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Training wide residual networks for deployment using a single bit for each weight
2018 · McDonnell, Mark D. · arXiv (Cornell University) · 64
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Characterization of Young and Old Adult Brains: An EEG Functional Connectivity Analysis
2019 · Bahar Moezzi, Latha Madhuri Pratti, et al. · Neuroscience · 63
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A Characterization of Suprathreshold Stochastic Resonance in an Array of Comparators by Correlation Coefficient
2002 · MARK D. MCDONNELL, DEREK ABBOTT, et al. · Fluctuation and Noise Letters · 55
Too good to be true: when overwhelming evidence fails to convince
2016 · Lachlan J. Gunn, François Chapeau-Blondeau, et al. · Proceedings of the Royal Society A Mathematical Physical and Engineering Sciences · 47
Neural Population Coding Is Optimized by Discrete Tuning Curves
2009 · Alexander P. Nikitin, Nigel G. Stocks, et al. · Physical Review Letters · 44
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Optimal stimulus and noise distributions for information transmission via suprathreshold stochastic resonance
2007 · Mark D. McDonnell, Nigel G. Stocks, et al. · Physical Review E · 43
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A deep convolutional neural network for segmentation of whole-slide pathology images identifies novel tumour cell-perivascular niche interactions that are associated with poor survival in glioblastoma
2021 · Amin Zadeh Shirazi, Mark D. McDonnell, et al. · British Journal of Cancer · 42
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Is electrical noise useful? [Point of View]
2011 · M D McDonnell · Proceedings of the IEEE · 42
Works count: 168
Citation count: 7,901
H-index: 32
I10-index: 64
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