Mark D. McDonnell

Publication Activity (10 Years)

Years Active: 2004-2024
Publications (10 Years): 39

Top Topics

Convolutional Neural Networks

Conjugate Gradient

Extreme Learning Machines

Top Venues

Publications

Mark D. McDonnell, Dong Gong, Ehsan Abbasnejad, Anton van den Hengel
Premonition: Using Generative Models to Preempt Future Data Changes in Continual Learning. CoRR (2024)
Mark C. McKenzie, Mark D. McDonnell
Hyperparameter Selection in Reinforcement Learning Using the "Design of Experiments" Method. INNS DLIA@IJCNN (2023)
Mark D. McDonnell, Dong Gong, Amin Parvaneh, Ehsan Abbasnejad, Anton van den Hengel
RanPAC: Random Projections and Pre-trained Models for Continual Learning. CoRR (2023)
Mark D. McDonnell, Dong Gong, Amin Parvaneh, Ehsan Abbasnejad, Anton van den Hengel
RanPAC: Random Projections and Pre-trained Models for Continual Learning. NeurIPS (2023)
Mark McKenzie, Mark D. McDonnell
Modern Value Based Reinforcement Learning: A Chronological Review. IEEE Access 10 (2022)
Namrata Nath, Sang-Heon Lee, Mark D. McDonnell, Ivan Lee
The quest for better clinical word vectors: Ontology based and lexical vector augmentation versus clinical contextual embeddings. Comput. Biol. Medicine 134 (2021)
Eriita G. Jones, Sebastien C. Wong, Anthony Milton, Joseph Sclauzero, Holly Whittenbury, Mark D. McDonnell
The Impact of Pan-Sharpening and Spectral Resolution on Vineyard Segmentation through Machine Learning. Remote. Sens. 12 (6) (2020)
Wei Gao, Ahmad Hashemi-Sakhtsari, Mark D. McDonnell
End-to-End Phoneme Recognition using Models from Semantic Image Segmentation. IJCNN (2020)
Mark D. McDonnell, Wei Gao
Acoustic Scene Classification Using Deep Residual Networks with Late Fusion of Separated High and Low Frequency Paths. ICASSP (2020)
Mark D. McDonnell, Hesham Mostafa, Runchun Wang, André van Schaik
Single-Bit-per-Weight Deep Convolutional Neural Networks without Batch-Normalization Layers for Embedded Systems. ACIRS (2019)
Iqbal Madakkatel, Belinda A. Chiera, Mark D. McDonnell
Predicting Financial Well-Being Using Observable Features and Gradient Boosting. Australasian Conference on Artificial Intelligence (2019)
Mark D. McDonnell, Bahar Moezzi, Russell S. A. Brinkworth
Using Style-Transfer to Understand Material Classification for Robotic Sorting of Recycled Beverage Containers. DICTA (2019)
Rapeeporn Chamchong, Wei Gao, Mark D. McDonnell
Thai Handwritten Recognition on Text Block-Based from Thai Archive Manuscripts. ICDAR (2019)
Mark McKenzie, Mark D. McDonnell
Degradation of Performance in Reinforcement Learning with State Measurement Uncertainty. MilCIS (2019)
Mark D. McDonnell, Hesham Mostafa, Runchun Wang, André van Schaik
Single-bit-per-weight deep convolutional neural networks without batch-normalization layers for embedded systems. CoRR (2019)
Lachlan J. Gunn, Peter Smet, Edward Arbon, Mark D. McDonnell
Anomaly Detection in Satellite Communications Systems using LSTM Networks. MilCIS (2018)
Victor Stamatescu, Mark D. McDonnell
Diagnosing Convolutional Neural Networks using Their Spectral Response. DICTA (2018)
Victor Stamatescu, Mark D. McDonnell
Diagnosing Convolutional Neural Networks using their Spectral Response. CoRR (2018)
Mark D. McDonnell
Training wide residual networks for deployment using a single bit for each weight. ICLR (Poster) (2018)
Samya Bagchi, Mark D. McDonnell
A model of neurobiologically plausible least-squares learning in visual cortex. IJCNN (2018)
Mark D. McDonnell
Training wide residual networks for deployment using a single bit for each weight. CoRR (2018)
Xiao Gao, David B. Grayden, Mark D. McDonnell
Modeling Electrode Place Discrimination in Cochlear Implant Stimulation. IEEE Trans. Biomed. Eng. 64 (9) (2017)
Mahmood Yousefi-Azar, Mark D. McDonnell
Semi-supervised convolutional extreme learning machine. IJCNN (2017)
Sebastien C. Wong, Victor Stamatescu, Adam Gatt, David A. Kearney, Ivan Lee, Mark D. McDonnell
Track Everything: Limiting Prior Knowledge in Online Multi-Object Recognition. CoRR (2017)
Wei Gao, Mark D. McDonnell
Analysis of Gradient Degradation and Feature Map Quality in Deep All-Convolutional Neural Networks Compared to Deep Residual Networks. ICONIP (2) (2017)
Mahmood Yousefi-Azar, Len Hamey, Vijay Varadharajan, Mark D. McDonnell
Fast, Automatic and Scalable Learning to Detect Android Malware. ICONIP (5) (2017)
Sebastien C. Wong, Victor Stamatescu, Adam Gatt, David A. Kearney, Ivan Lee, Mark D. McDonnell
Track Everything: Limiting Prior Knowledge in Online Multi-Object Recognition. IEEE Trans. Image Process. 26 (10) (2017)
Mark D. McDonnell, Bruce P. Graham
Phase changes in neuronal postsynaptic spiking due to short term plasticity. PLoS Comput. Biol. 13 (9) (2017)
Philip de Chazal, Mark D. McDonnell
Regularized training of the extreme learning machine using the conjugate gradient method. IJCNN (2017)
Migel D. Tissera, Mark D. McDonnell
Deep extreme learning machines: supervised autoencoding architecture for classification. Neurocomputing 174 (2016)
Philip de Chazal, Mark D. McDonnell
Efficient computation of the Levenberg-Marquardt algorithm for feedforward networks with linear outputs. IJCNN (2016)
Migel D. Tissera, Mark D. McDonnell
Enhancing deep extreme learning machines by error backpropagation. IJCNN (2016)
Sebastien C. Wong, Adam Gatt, Victor Stamatescu, Mark D. McDonnell
Understanding data augmentation for classification: when to warp? CoRR (2016)
Daniel E. Padilla, Mark D. McDonnell
Integrating convolutional neural networks into a sparse distributed representation model based on mammalian cortical learning. IJCNN (2016)
Mark D. McDonnell, Joshua H. Goldwyn, Benjamin Lindner
Editorial: Neuronal Stochastic Variability: Influences on Spiking Dynamics and Network Activity. Frontiers Comput. Neurosci. 10 (2016)
Migel D. Tissera, Mark D. McDonnell
Modular expansion of the hidden layer in Single Layer Feedforward neural Networks. IJCNN (2016)
Sebastien C. Wong, Adam Gatt, Victor Stamatescu, Mark D. McDonnell
Understanding Data Augmentation for Classification: When to Warp? DICTA (2016)
Mark D. McDonnell, Robby G. McKilliam, Philip de Chazal
On the importance of pair-wise feature correlations for image classification. IJCNN (2016)
Bahar Moezzi, Nicolangelo Iannella, Mark D. McDonnell
Ion channel noise can explain firing correlation in auditory nerves. J. Comput. Neurosci. 41 (2) (2016)
Mark D. McDonnell, Tony Vladusich
Enhanced Image Classification With a Fast-Learning Shallow Convolutional Neural Network. CoRR (2015)
Mark D. McDonnell, Tony Vladusich
Enhanced image classification with a fast-learning shallow convolutional neural network. IJCNN (2015)
Xiao Gao, David B. Grayden, Mark D. McDonnell
Modeling electrode place discrimination in cochlear implants: Analysis of the influence of electrode array insertion depth. NER (2015)
Priscilla E. Greenwood, Mark D. McDonnell, Lawrence M. Ward
Dynamics of Gamma Bursts in Local Field Potentials. Neural Comput. 27 (1) (2015)
Siyi Wang, Weisi Guo, Mark D. McDonnell
Downlink Interference Estimation without Feedback for Heterogeneous Network Interference Avoidance. CoRR (2014)
Siyi Wang, Weisi Guo, Song Qiu, Mark D. McDonnell
Performance of Macro-Scale Molecular Communications with Sensor Cleanse Time. CoRR (2014)
Siyi Wang, Weisi Guo, Mark D. McDonnell
Distance distributions for real cellular networks. INFOCOM Workshops (2014)
Daniel E. Padilla, Mark D. McDonnell
A Neurobiologically Plausible Vector Symbolic Architecture. ICSC (2014)
Siyi Wang, Weisi Guo, Song Qiu, Mark D. McDonnell
Performance of macro-scale molecular communications with sensor cleanse time. ICT (2014)
Siyi Wang, Weisi Guo, Mark D. McDonnell
Downlink interference estimation without feedback for heterogeneous network interference avoidance. ICT (2014)
Mark D. McDonnell, Migel D. Tissera, André van Schaik, Jonathan Tapson
Fast, simple and accurate handwritten digit classification using extreme learning machines with shaped input-weights. CoRR (2014)
Siyi Wang, Weisi Guo, Mark D. McDonnell
Distance Distributions for Real Cellular Networks. CoRR (2014)
Xiao Gao, David B. Grayden, Mark D. McDonnell
Inferring the dynamic range of electrode current by using an information theoretic model of cochlear implant stimulation. ITW (2014)
Migel D. Tissera, Mark D. McDonnell
Enabling 'Question Answering' in the MBAT Vector Symbolic Architecture by Exploiting Orthogonal Random Matrices. ICSC (2014)
Mark D. McDonnell, Kwabena Boahen, Auke Jan Ijspeert, Terrence J. Sejnowski
Engineering intelligent electronic systems based on computational neuroscience [scanning the issue]. Proc. IEEE 102 (5) (2014)
Bahar Moezzi, Nicolangelo Iannella, Mark D. McDonnell
Modelling the influence of short term depression in vesicle release and stochastic calcium channel gating on auditory nerve spontaneous firing statistics. Frontiers Comput. Neurosci. 8 (2014)
Siyi Wang, Weisi Guo, Mark D. McDonnell
Transmit pulse shaping for molecular communications. INFOCOM Workshops (2014)
Xiao Gao, David B. Grayden, Mark D. McDonnell
Using convex optimization to compute channel capacity in a channel model of cochlear implant stimulation. ISIT (2014)
Siyi Wang, Weisi Guo, Mark D. McDonnell
Transmit Pulse Shaping for Molecular Communications. CoRR (2014)
Xiao Gao, David B. Grayden, Mark D. McDonnell
Information theoretic optimization of cochlear implant electrode usage probabilities. EMBC (2013)
Lubomir Kostal, Petr Lánský, Mark D. McDonnell
Metabolic cost of neuronal information in an empirical stimulus-response model. Biol. Cybern. 107 (3) (2013)
Mark D. McDonnell, Ashutosh Mohan, Christian Stricker
Mathematical analysis and algorithms for efficiently and accurately implementing stochastic simulations of short-term synaptic depression and facilitation. Frontiers Comput. Neurosci. 7 (2013)
Ashutosh Mohan, Mark D. McDonnell, Christian Stricker
Interaction of short-term depression and firing dynamics in shaping single neuron encoding. Frontiers Comput. Neurosci. 7 (2013)
Mark D. McDonnell, Lawrence M. Ward
Identifying positive roles for endogenous stochastic noise during computation in neural systems. EMBC (2013)
Alexey S. Moroz, Mark D. McDonnell, Anthony N. Burkitt, David B. Grayden, Hamish Meffin
Information theoretic inference of the optimal number of electrodes for future cochlear implants using a spiral cochlea model. EMBC (2012)
Mark D. McDonnell
Is electrical noise useful? [Point of View]. Proc. IEEE 99 (2) (2011)
Mark D. McDonnell, Shiro Ikeda, Jonathan H. Manton
An introductory review of information theory in the context of computational neuroscience. Biol. Cybern. 105 (1) (2011)
Mark D. McDonnell, Shiro Ikeda, Jonathan H. Manton
An Introductory Review of Information Theory in the Context of Computational Neuroscience CoRR (2011)
Brenton J. Prettejohn, Matthew J. Berryman, Mark D. McDonnell
Methods for Generating Complex Networks with Selected Structural Properties for Simulations: A Review and Tutorial for Neuroscientists. Frontiers Comput. Neurosci. 5 (2011)
Mark D. McDonnell, Anthony N. Burkitt, David B. Grayden, Hamish Meffin, Alex J. Grant
A channel model for inferring the optimal number of electrodes for future cochlear implants. IEEE Trans. Inf. Theory 56 (2) (2010)
Mark D. McDonnell, Nigel G. Stocks, Pierre-Olivier Amblard
Communication of uncoded sensor measurements through nanoscale binary-node stochastic pooling networks. Nano Commun. Networks 1 (3) (2010)
Mark D. McDonnell, Adrian P. Flitney
Signal acquisition via polarization modulation in single photon sources. CoRR (2009)
Mark D. McDonnell, Derek Abbott
What Is Stochastic Resonance? Definitions, Misconceptions, Debates, and Its Relevance to Biology. PLoS Comput. Biol. 5 (5) (2009)
Mark D. McDonnell, Nigel G. Stocks
Suprathreshold stochastic resonance. Scholarpedia 4 (6) (2009)
Mark D. McDonnell, Derek Abbott
Signal reconstruction via noise through a system of parallel threshold nonlinearities. ICASSP (2) (2004)
Mark D. McDonnell, Derek Abbott
Optimal quantization in neural coding. ISIT (2004)