Mark D. McDonnell

Orcid: 0000-0002-7009-3869

According to our database1, Mark D. McDonnell authored at least 63 papers between 2004 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Premonition: Using Generative Models to Preempt Future Data Changes in Continual Learning.
CoRR, 2024

2023
RanPAC: Random Projections and Pre-trained Models for Continual Learning.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Hyperparameter Selection in Reinforcement Learning Using the "Design of Experiments" Method.
Proceedings of the International Neural Network Society Workshop on Deep Learning Innovations and Applications, 2023

2022
Modern Value Based Reinforcement Learning: A Chronological Review.
IEEE Access, 2022

2021
The quest for better clinical word vectors: Ontology based and lexical vector augmentation versus clinical contextual embeddings.
Comput. Biol. Medicine, 2021

2020
The Impact of Pan-Sharpening and Spectral Resolution on Vineyard Segmentation through Machine Learning.
Remote. Sens., 2020

End-to-End Phoneme Recognition using Models from Semantic Image Segmentation.
Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

Acoustic Scene Classification Using Deep Residual Networks with Late Fusion of Separated High and Low Frequency Paths.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

2019
Degradation of Performance in Reinforcement Learning with State Measurement Uncertainty.
Proceedings of the 2019 Military Communications and Information Systems Conference, 2019

Thai Handwritten Recognition on Text Block-Based from Thai Archive Manuscripts.
Proceedings of the 2019 International Conference on Document Analysis and Recognition, 2019

Using Style-Transfer to Understand Material Classification for Robotic Sorting of Recycled Beverage Containers.
Proceedings of the 2019 Digital Image Computing: Techniques and Applications, 2019

Predicting Financial Well-Being Using Observable Features and Gradient Boosting.
Proceedings of the AI 2019: Advances in Artificial Intelligence, 2019

Single-Bit-per-Weight Deep Convolutional Neural Networks without Batch-Normalization Layers for Embedded Systems.
Proceedings of the 4th Asia-Pacific Conference on Intelligent Robot Systems, 2019

2018
Anomaly Detection in Satellite Communications Systems using LSTM Networks.
Proceedings of the 2018 Military Communications and Information Systems Conference, 2018

A model of neurobiologically plausible least-squares learning in visual cortex.
Proceedings of the 2018 International Joint Conference on Neural Networks, 2018

Training wide residual networks for deployment using a single bit for each weight.
Proceedings of the 6th International Conference on Learning Representations, 2018

Diagnosing Convolutional Neural Networks using Their Spectral Response.
Proceedings of the 2018 Digital Image Computing: Techniques and Applications, 2018

2017
Track Everything: Limiting Prior Knowledge in Online Multi-Object Recognition.
IEEE Trans. Image Process., 2017

Modeling Electrode Place Discrimination in Cochlear Implant Stimulation.
IEEE Trans. Biomed. Eng., 2017

Phase changes in neuronal postsynaptic spiking due to short term plasticity.
PLoS Comput. Biol., 2017

Semi-supervised convolutional extreme learning machine.
Proceedings of the 2017 International Joint Conference on Neural Networks, 2017

Regularized training of the extreme learning machine using the conjugate gradient method.
Proceedings of the 2017 International Joint Conference on Neural Networks, 2017

Fast, Automatic and Scalable Learning to Detect Android Malware.
Proceedings of the Neural Information Processing - 24th International Conference, 2017

Analysis of Gradient Degradation and Feature Map Quality in Deep All-Convolutional Neural Networks Compared to Deep Residual Networks.
Proceedings of the Neural Information Processing - 24th International Conference, 2017

2016
Ion channel noise can explain firing correlation in auditory nerves.
J. Comput. Neurosci., 2016

Deep extreme learning machines: supervised autoencoding architecture for classification.
Neurocomputing, 2016

Editorial: Neuronal Stochastic Variability: Influences on Spiking Dynamics and Network Activity.
Frontiers Comput. Neurosci., 2016

Modular expansion of the hidden layer in Single Layer Feedforward neural Networks.
Proceedings of the 2016 International Joint Conference on Neural Networks, 2016

Enhancing deep extreme learning machines by error backpropagation.
Proceedings of the 2016 International Joint Conference on Neural Networks, 2016

Integrating convolutional neural networks into a sparse distributed representation model based on mammalian cortical learning.
Proceedings of the 2016 International Joint Conference on Neural Networks, 2016

On the importance of pair-wise feature correlations for image classification.
Proceedings of the 2016 International Joint Conference on Neural Networks, 2016

Efficient computation of the Levenberg-Marquardt algorithm for feedforward networks with linear outputs.
Proceedings of the 2016 International Joint Conference on Neural Networks, 2016

Understanding Data Augmentation for Classification: When to Warp?
Proceedings of the 2016 International Conference on Digital Image Computing: Techniques and Applications, 2016

2015
Dynamics of Gamma Bursts in Local Field Potentials.
Neural Comput., 2015

Modeling electrode place discrimination in cochlear implants: Analysis of the influence of electrode array insertion depth.
Proceedings of the 7th International IEEE/EMBS Conference on Neural Engineering, 2015

Enhanced image classification with a fast-learning shallow convolutional neural network.
Proceedings of the 2015 International Joint Conference on Neural Networks, 2015

2014
Engineering intelligent electronic systems based on computational neuroscience [scanning the issue].
Proc. IEEE, 2014

Modelling the influence of short term depression in vesicle release and stochastic calcium channel gating on auditory nerve spontaneous firing statistics.
Frontiers Comput. Neurosci., 2014

Fast, simple and accurate handwritten digit classification using extreme learning machines with shaped input-weights.
CoRR, 2014

Enabling 'Question Answering' in the MBAT Vector Symbolic Architecture by Exploiting Orthogonal Random Matrices.
Proceedings of the 2014 IEEE International Conference on Semantic Computing, 2014

A Neurobiologically Plausible Vector Symbolic Architecture.
Proceedings of the 2014 IEEE International Conference on Semantic Computing, 2014

Inferring the dynamic range of electrode current by using an information theoretic model of cochlear implant stimulation.
Proceedings of the 2014 IEEE Information Theory Workshop, 2014

Using convex optimization to compute channel capacity in a channel model of cochlear implant stimulation.
Proceedings of the 2014 IEEE International Symposium on Information Theory, Honolulu, HI, USA, June 29, 2014

Transmit pulse shaping for molecular communications.
Proceedings of the 2014 Proceedings IEEE INFOCOM Workshops, Toronto, ON, Canada, April 27, 2014

Distance distributions for real cellular networks.
Proceedings of the 2014 Proceedings IEEE INFOCOM Workshops, Toronto, ON, Canada, April 27, 2014

Performance of macro-scale molecular communications with sensor cleanse time.
Proceedings of the 21st International Conference on Telecommunications, 2014

Downlink interference estimation without feedback for heterogeneous network interference avoidance.
Proceedings of the 21st International Conference on Telecommunications, 2014

2013
Interaction of short-term depression and firing dynamics in shaping single neuron encoding.
Frontiers Comput. Neurosci., 2013

Mathematical analysis and algorithms for efficiently and accurately implementing stochastic simulations of short-term synaptic depression and facilitation.
Frontiers Comput. Neurosci., 2013

Metabolic cost of neuronal information in an empirical stimulus-response model.
Biol. Cybern., 2013

Identifying positive roles for endogenous stochastic noise during computation in neural systems.
Proceedings of the 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2013

Information theoretic optimization of cochlear implant electrode usage probabilities.
Proceedings of the 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2013

2012
Information theoretic inference of the optimal number of electrodes for future cochlear implants using a spiral cochlea model.
Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2012

2011
Is electrical noise useful? [Point of View].
Proc. IEEE, 2011

Methods for Generating Complex Networks with Selected Structural Properties for Simulations: A Review and Tutorial for Neuroscientists.
Frontiers Comput. Neurosci., 2011

An introductory review of information theory in the context of computational neuroscience.
Biol. Cybern., 2011

2010
A channel model for inferring the optimal number of electrodes for future cochlear implants.
IEEE Trans. Inf. Theory, 2010

Communication of uncoded sensor measurements through nanoscale binary-node stochastic pooling networks.
Nano Commun. Networks, 2010

2009
Suprathreshold stochastic resonance.
Scholarpedia, 2009

What Is Stochastic Resonance? Definitions, Misconceptions, Debates, and Its Relevance to Biology.
PLoS Comput. Biol., 2009

Signal acquisition via polarization modulation in single photon sources.
CoRR, 2009

2004
Optimal quantization in neural coding.
Proceedings of the 2004 IEEE International Symposium on Information Theory, 2004

Signal reconstruction via noise through a system of parallel threshold nonlinearities.
Proceedings of the 2004 IEEE International Conference on Acoustics, 2004


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