Prof. Mark Coates Profile

Prof. Mark Coates

Professor at McGill Univ

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Publications (6)

Proceedings Article | 9 September 2019 Paper

Estimation of time-series on graphs using Bayesian graph convolutional neural networks

Fatemeh Teimury, Soumyasundar Pal, Arezou Amini, Mark Coates

Proceedings Volume 11138, 111380Y (2019) https://doi.org/10.1117/12.2530046

KEYWORDS: Neural networks, Convolutional neural networks, Monte Carlo methods, Bayesian inference, Convolution, Data modeling

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Proceedings Article | 2 May 2017 Paper

Particle flow superpositional GLMB filter

Augustin-Alexandru Saucan, Yunpeng Li, Mark Coates

Proceedings Volume 10200, 102000F (2017) https://doi.org/10.1117/12.2263236

KEYWORDS: Particles, Particle filters, Filtering (signal processing), Electronic filtering, Sensors, Monte Carlo methods, Lithium, Target detection, Thermal weapon sites, Gaussian filters

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Proceedings Article | 17 May 2016 Paper

Gaussian particle flow implementation of PHD filter

Lingling Zhao, Junjie Wang, Yunpeng Li, Mark Coates

Proceedings Volume 9842, 98420D (2016) https://doi.org/10.1117/12.2228326

KEYWORDS: Particles, Gaussian filters, Numerical simulations, Detection and tracking algorithms, Target detection, Monte Carlo methods, Filtering (signal processing), Error analysis, Sensors, Nonlinear dynamics

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Proceedings Article | 21 May 2015 Paper

A distributed general multi-sensor cardinalized probability hypothesis density (CPHD) filter for sensor networks

S. Datta Gupta, S. Nannuru, M. Coates, M. Rabbat

Proceedings Volume 9474, 94740F (2015) https://doi.org/10.1117/12.2177502

KEYWORDS: Sensors, Probability theory, Sensor networks, Target detection, Astatine, Detection and tracking algorithms, Model-based design, Bismuth, Solids, Platinum

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Proceedings Article | 20 June 2014 Paper

Hybrid multi-Bernoulli CPHD filter for superpositional sensors

Santosh Nannuru, Mark Coates

Proceedings Volume 9091, 90910D (2014) https://doi.org/10.1117/12.2050158

KEYWORDS: Sensors, Particles, Motion models, Error analysis, Target recognition, Virtual colonoscopy, Computer simulations, Detection and tracking algorithms, Standards development, Instrument modeling

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Showing 5 of 6 publications

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