Mark D. McDonnell
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Australian mathematician and engineer
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Mark D. McDonnellengineering Degrees
Engineering
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Mark D. McDonnellmathematics Degrees
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Applied Mathematics
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Why Is Mark D. McDonnell Influential?
(Suggest an Edit or Addition)According to Wikipedia, Mark Damian McDonnell is an electronic engineer and mathematician, notable for his work on stochastic resonance and more specifically suprathreshold stochastic resonance. Education McDonnell graduated from the Salesian College, Adelaide. He received a BSc in Mathematical & Computer Sciences , a BE in Electrical & Electronic Engineering , and a BSc in Applied Mathematics all from The University of Adelaide, Australia. He received his PhD in Electrical & Electronic Engineering , under Derek Abbott and Charles E. M. Pearce, also from the University of Adelaide, for a thesis entitled Theoretical Aspects of Stochastic Signal Quantisation and Suprathreshold Stochastic Resonance. During the course of his PhD, he was also a visiting scholar at the University of Warwick, UK, under Nigel G. Stocks.
Mark D. McDonnell's Published Works
Number of citations in a given year to any of this author's works
Total number of citations to an author for the works they published in a given year. This highlights publication of the most important work(s) by the author
Published Works
- Understanding Data Augmentation for Classification: When to Warp? (2016) (731)
- What Is Stochastic Resonance? Definitions, Misconceptions, Debates, and Its Relevance to Biology (2009) (676)
- The benefits of noise in neural systems: bridging theory and experiment (2011) (594)
- Mathematical Methods for Spatially Cohesive Reserve Design (2002) (269)
- Stochastic Resonance: From Suprathreshold Stochastic Resonance to Stochastic Signal Quantization (2008) (236)
- Deep extreme learning machines: supervised autoencoding architecture for classification (2016) (106)
- Methods for Generating Complex Networks with Selected Structural Properties for Simulations: A Review and Tutorial for Neuroscientists (2011) (86)
- Enhanced image classification with a fast-learning shallow convolutional neural network (2015) (79)
- Optimal information transmission in nonlinear arrays through suprathreshold stochastic resonance (2006) (74)
- Fast, Simple and Accurate Handwritten Digit Classification by Training Shallow Neural Network Classifiers with the ‘Extreme Learning Machine’ Algorithm (2015) (74)
- 25th Annual Computational Neuroscience Meeting: CNS-2016 (2016) (71)
- Acoustic Scene Classification Using Deep Residual Networks with Late Fusion of Separated High and Low Frequency Paths (2020) (68)
- Training wide residual networks for deployment using a single bit for each weight (2018) (67)
- An analysis of noise enhanced information transmission in an array of comparators (2002) (66)
- A characterization of suprathreshold stochastic resonance in an array of comparators by correlation coefficient (2002) (56)
- Maximally informative stimuli and tuning curves for sigmoidal rate-coding neurons and populations. (2008) (56)
- Optimal stimulus and noise distributions for information transmission via suprathreshold stochastic resonance. (2007) (45)
- Neural population coding is optimized by discrete tuning curves. (2008) (44)
- An introductory review of information theory in the context of computational neuroscience (2011) (38)
- Is electrical noise useful? [Point of View] (2011) (34)
- Stochastic pooling networks (2009) (33)
- Randomized switching in the two-envelope problem (2009) (30)
- Quantization in the presence of large amplitude threshold noise (2005) (28)
- Metabolic cost of neuronal information in an empirical stimulus-response model (2013) (27)
- Characterization of Young and Old Adult Brains: An EEG Functional Connectivity Analysis (2018) (24)
- Channel-noise-induced stochastic facilitation in an auditory brainstem neuron model. (2013) (22)
- Too good to be true: when overwhelming evidence fails to convince (2016) (22)
- Track Everything: Limiting Prior Knowledge in Online Multi-Object Recognition (2017) (22)
- The Application of Deep Convolutional Neural Networks to Brain Cancer Images: A Survey (2020) (21)
- Transmit pulse shaping for molecular communications (2014) (21)
- The Impact of Pan-Sharpening and Spectral Resolution on Vineyard Segmentation through Machine Learning (2020) (19)
- Suprathreshold stochastic resonance (2000) (19)
- A review of methods for identifying stochastic resonance in simulations of single neuron models (2015) (19)
- Motif-Role-Fingerprints: The Building-Blocks of Motifs, Clustering-Coefficients and Transitivities in Directed Networks (2014) (18)
- Performance of a hierarchical temporal memory network in noisy sequence learning (2013) (18)
- Engineering intelligent electronic systems based on computational neuroscience [scanning the issue] (2014) (18)
- Dynamics of Gamma Bursts in Local Field Potentials (2015) (18)
- Gain from the two-envelope problem via information asymmetry: on the suboptimality of randomized switching (2011) (18)
- Stochastic resonance and data processing inequality (2003) (17)
- Performance of macro-scale molecular communications with sensor cleanse time (2014) (15)
- Cancer Tissue Classification Using Supervised Machine Learning Applied to MALDI Mass Spectrometry Imaging (2021) (14)
- Information capacity of stochastic pooling networks is achieved by discrete inputs. (2009) (14)
- 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) (13)
- Fast, simple and accurate handwritten digit classification using extreme learning machines with shaped input-weights (2014) (13)
- Small Modifications to Network Topology Can Induce Stochastic Bistable Spiking Dynamics in a Balanced Cortical Model (2014) (12)
- Analog-to-digital conversion using suprathreshold stochastic resonance (2005) (12)
- A Channel Model for Inferring the Optimal Number of Electrodes for Future Cochlear Implants (2010) (12)
- Point singularities and suprathreshold stochastic resonance in optimal coding (2004) (12)
- Stochastic Resonance: Index (2008) (12)
- 26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3 (2017) (11)
- Decoding suprathreshold stochastic resonance with optimal weights (2015) (11)
- Ion channel noise can explain firing correlation in auditory nerves (2016) (10)
- Downlink interference estimation without feedback for heterogeneous network interference avoidance (2014) (10)
- Stochastic Resonance: List of figures (2008) (10)
- Input-rate modulation of gamma oscillations is sensitive to network topology, delays and short-term plasticity (2012) (10)
- Editorial: Neuronal Stochastic Variability: Influences on Spiking Dynamics and Network Activity (2016) (10)
- Optimal weighted suprathreshold stochastic resonance with multigroup saturating sensors (2016) (10)
- Semi-supervised convolutional extreme learning machine (2017) (9)
- Theoretical aspects of stochastic signal quantisation and suprathreshold stochastic resonance. (2006) (9)
- Pooling networks for a discrimination task: noise-enhanced detection (2007) (9)
- Modeling the influence of short term depression in vesicle release and stochastic calcium channel gating on auditory nerve spontaneous firing statistics (2014) (9)
- Stochastic information transfer from cochlear implant electrodes to auditory nerve fibers. (2014) (9)
- A Kuramoto coupling of quasi-cycle oscillators with application to neural networks (2016) (9)
- Modeling Electrode Place Discrimination in Cochlear Implant Stimulation (2017) (8)
- Deep Extreme Learning Machines for Classification (2015) (8)
- Phase changes in neuronal postsynaptic spiking due to short term plasticity (2017) (8)
- Anomaly Detection in Satellite Communications Systems using LSTM Networks (2018) (8)
- Signal reconstruction via noise through a system of parallel threshold nonlinearities (2004) (8)
- Adaptive recursive algorithm for optimal weighted suprathreshold stochastic resonance (2017) (7)
- Using noise to break the noise barrier in circuits (2005) (7)
- Neural mechanisms for analog-to-digital conversion (2004) (7)
- Simulation of electromyographic recordings following transcranial magnetic stimulation. (2018) (7)
- Distance distributions for real cellular networks (2014) (7)
- Generalized noise resonance: using noise for signal enhancement (2004) (6)
- Combining machine learning and conventional statistical approaches for risk factor discovery in a large cohort study (2021) (6)
- Interaction of short-term depression and firing dynamics in shaping single neuron encoding (2013) (6)
- Thai Handwritten Recognition on Text Block-Based from Thai Archive Manuscripts (2019) (6)
- Optimising threshold levels for information transmission in binary threshold networks: Independent multiplicative noise on each threshold (2015) (6)
- M-ary suprathreshold stochastic resonance: Generalization and scaling beyond binary threshold nonlinearities (2014) (6)
- Information theoretic optimization of cochlear implant electrode usage probabilities (2013) (6)
- Fast, Automatic and Scalable Learning to Detect Android Malware (2017) (6)
- Modular expansion of the hidden layer in Single Layer Feedforward neural Networks (2016) (5)
- M-ary suprathreshold stochastic resonance in multilevel threshold systems with signal-dependent noise (2017) (5)
- Effect of network topology in opinion formation models (2009) (5)
- Enhancing deep extreme learning machines by error backpropagation (2016) (5)
- Machine Learning Quantitation of Cardiovascular and Cerebrovascular Disease: A Systematic Review of Clinical Applications (2021) (5)
- Regularized training of the extreme learning machine using the conjugate gradient method (2017) (5)
- Information theoretic inference of the optimal number of electrodes for future cochlear implants using a spiral cochlea model (2012) (5)
- Optimal sensor selection for noisy binary detection in stochastic pooling networks. (2013) (5)
- Bio-inspired communication: performance limits for information transmission and compression in stochastic pooling networks with binary quantizing nodes (2010) (4)
- On the importance of pair-wise feature correlations for image classification (2016) (4)
- Applying Stochastic Signal Quantization Theory to the Robust Digitization of Noisy Analog Signals (2009) (4)
- Mathematical analysis and algorithms for efficiently and accurately implementing stochastic simulations of short-term synaptic depression and facilitation (2013) (4)
- Reliable communication and sensing via parallel redundancy in noisy digital receivers (2008) (4)
- Open Questions For Suprathreshold Stochastic Resonance In Sensory Neural Models for Motion Detection Using Artificial Insect Vision (2003) (3)
- A Neurobiologically Plausible Vector Symbolic Architecture (2014) (3)
- Modeling electrode place discrimination in cochlear implants: Analysis of the influence of electrode array insertion depth (2015) (3)
- Cross-spectral measurement of neural signal transfer (2004) (3)
- Maximally Informative Stimuli and Tuning Curves for Sigmoidal Rate-Coding Neurons with Quasi-Poisson Variability (2008) (3)
- Enabling 'Question Answering' in the MBAT Vector Symbolic Architecture by Exploiting Orthogonal Random Matrices (2014) (3)
- Inferring the dynamic range of electrode current by using an information theoretic model of cochlear implant stimulation (2014) (3)
- Learned filters for object detection in multi-object visual tracking (2016) (3)
- Signal Estimation Via Averaging of Coarsely Quantised Signals (2007) (2)
- LOW-COMPLEXITY ACOUSTIC SCENE CLASSIFICATION USING ONE-BIT-PER-WEIGHT DEEP CONVOLUTIONAL NEURAL NETWORKS Technical Report (2020) (2)
- Communication of uncoded sensor measurements through nanoscale binary-node stochastic pooling networks (2010) (2)
- Signal acquisition via polarization modulation in single photon sources (2009) (2)
- A model of the effects of authority on consensus formation in adaptive networks: Impact on network topology and robustness (2013) (2)
- Signal compression in biological sensory systems: information theoretic performance limits (2007) (2)
- A biologically inspired model for signal compression (2006) (2)
- High-resolution optimal quantization for stochastic pooling networks (2006) (2)
- Optimal quantization for energy-efficient information transfer in a population of neuron-like devices (2004) (2)
- Diagnosing Convolutional Neural Networks using Their Spectral Response (2018) (2)
- Unifying information theory and machine learning in a model of electrode discrimination in cochlear implants (2021) (2)
- Single-Bit-per-Weight Deep Convolutional Neural Networks without Batch-Normalization Layers for Embedded Systems (2019) (2)
- Degradation of Performance in Reinforcement Learning with State Measurement Uncertainty (2019) (2)
- Using Style-Transfer to Understand Material Classification for Robotic Sorting of Recycled Beverage Containers (2019) (2)
- Neural information transfer in a noisy environment (2001) (2)
- Natural moment-to-moment signal variability and stochastic facilitation (2011) (1)
- Stochastic Resonance: Suprathreshold stochastic resonance: encoding (2008) (1)
- How to use noise to reduce complexity in quantization (2005) (1)
- Stochastic Resonance: Stochastic resonance: its definition, history, and debates (2008) (1)
- Optimal quantization in neural coding (2004) (1)
- Using convex optimization to compute channel capacity in a channel model of cochlear implant stimulation (2014) (1)
- A Unified Account of Perceptual Layering and Surface Appearance in Terms of Gamut Relativity (2014) (1)
- Maximizing information transfer through nonlinear noisy devices (2002) (1)
- Optimal quantization and suprathreshold stochastic resonance (2005) (1)
- Identifying positive roles for endogenous stochastic noise during computation in neural systems (2013) (1)
- Data processing inequality and stochastic resonance (2003) (1)
- Efficient computation of the Levenberg-Marquardt algorithm for feedforward networks with linear outputs (2016) (1)
- The role of stochasticity in an information-optimal neural population code (2009) (1)
- SNDR enhancement in noisy sinusoidal signals by non-linear processing elements (2007) (0)
- Stochastic Resonance: SSR, neural coding, and performance tradeoffs (2008) (0)
- Publisher's Note: Channel-noise-induced stochastic facilitation in an auditory brainstem neuron model [Phys. Rev. E 88, 052722 (2013)] (2013) (0)
- Sensor selection for distributed detection via multiaccess channels (2009) (0)
- Ion channel noise can explain firing correlation in auditory nerves (2016) (0)
- Stochastic Resonance: Large N suprathreshold stochastic resonance (2008) (0)
- Metabolic cost of neuronal information in an empirical stimulus-response model (2013) (0)
- Stochastic Resonance: Introduction and motivation (2008) (0)
- Modern Value Based Reinforcement Learning: A Chronological Review (2022) (0)
- Planet four: A neural network’s search for polar spring-time fans on Mars (2022) (0)
- A biologically inspired approach to signal compression (2007) (0)
- Major League Baseball: Americas Recession-Proof Pastime (2010) (0)
- 25th Annual Computational Neuroscience Meeting: CNS-2016 (2016) (0)
- Distributed Bandpass Filtering and Signal Demodulation in Cortical Network Models (2014) (0)
- The perception of surface gray shades and the computational goals of human vision (2014) (0)
- Optimal coding of a random stimulus by a population of parallel neuron models (2007) (0)
- Matching synaptic type with postsynaptic firing class shapes the encoding of either stimulus rate or rate change (2011) (0)
- End-to-End Phoneme Recognition using Models from Semantic Image Segmentation (2020) (0)
- Stochastic Resonance: Suprathreshold stochastic resonance: large N encoding (2008) (0)
- Integrating convolutional neural networks into a sparse distributed representation model based on mammalian cortical learning (2016) (0)
- Stochastic Pooling Networks: A biologically inspired model for robust signal detection and compression (2008) (0)
- Stochastic Resonance: Preface (2008) (0)
- Optimal sigmoidal tuning curves for intensity encoding sensory neurons with quasi-Poisson variability (2008) (0)
- Analysis of Gradient Degradation and Feature Map Quality in Deep All-Convolutional Neural Networks Compared to Deep Residual Networks (2017) (0)
- Stochastic Resonance: The future of stochastic resonance and suprathreshold stochastic resonance (2008) (0)
- Stochastic Resonance: Stochastic resonance in the auditory system (2008) (0)
- Stochastic Resonance: References (2008) (0)
- CLASSIFICATION USING DEEP RESIDUAL NETWORKS WITH LATE FUSION OF SEPARATED HIGH AND LOW FREQUENCY PATHS Technical Report (2019) (0)
- A model of neurobiologically plausible least-squares learning in visual cortex (2018) (0)
- Abstract PO-004: A deep convolutional neural network for segmentation of whole-slide pathology images in glioblastoma (2021) (0)
- Stochastic Resonance: Optimal stochastic quantization (2008) (0)
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