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View: Publications | Selected presentations and lectures

Here you can find various publications and presentations and lectures by D.K.E. Green.

Research interests:

  • Probabilistic physical simulations
  • Probabilistic numerical methods
  • Bayesian inference
  • Uncertainty Quantification
  • Machine Learning and Artificial Intelligence for engineering applications


Probabilistic solution of chaotic dynamical system inverse problems using Bayesian Artificial Neural Networks

2020 - DKE Green, F Rindler - arXiv preprint


Probabilistic time series prediction

Probabilistic time series prediction using Machine Learning.

Model Inference for ordinary differential equations by parametric polynomial kernel regression

2019 - DKE Green, F Rindler - 3rd ECCOMAS Thematic Conference on Uncertainty Quantification in Computational Sciences and Engineering

doi:10.7712/120219.6340.18533 | arXiv:1908.02105

Example output from the UNCECOMP paper.

Prediction of a chaotic dynamical system from prior time series observations.

Probabilistic analysis for computational mechanics with applications in Civil Engineering

2017 - DKE Green - UNSW PhD Thesis


Probability threshold problem using a Gaussian mixture model

Demonstrating a probability threshold problem using a Gaussian mixture model.

Efficient Markov Chain Monte Carlo for combined Subset Simulation and nonlinear finite element analysis

2017 - DKE Green - Computer Methods in Applied Mechanics and Engineering


Finite element model displacement

Comparing performance of Markov Chain Monte Carlo and the Spectral Stochastic Finite Element Method for predicting the probability of a soil footing collapse.

The simulation and discretisation of random fields for probabilistic finite element analysis of soils using meshes of arbitrary triangular elements

2015 - DKE Green, K Douglas, G Mostyn - Computers and Geotechnics


Slope stability shear failure

Stress and strain analysis of a slope with probabilistically modelled strengths.

Earthquake stability assessment for open pit mine slopes

2013 - JCW Toh, DKE Green, GE Swarbrick, MJ Fowler, BE Estrada - International Symposium on Slope Stability in Open Pit Mining and Civil Engineering


Open-pit mine cross section

A cross section of the large open-pit mine simulated and analysed in this paper.

Selected presentations and lectures

Model inference for Ordinary Differential Equations by parametric polynomial kernel regression

2019 - DKE Green - UNCECOMP 2019 - Crete, Greece


Regression error comparison

Relative errors for different regression methods used in the presentation.

Aspects of Machine Learning for Engineering

2018 - DKE Green - University of Warwick - Coventry, UK


Example slide showing parametric model entropy

Understanding parametric Machine Learning models in terms of probabilistic numerics and information entropy.

Machine Learning for Infrastructure Monitoring

2018 - DKE Green - The Alan Turing Institute - London, UK


Example slide showing clustering methods

Slide discussing how clustering algorithms can be used for anomaly detection.

Probabilistic Computational Mechanics and Uncertainty Quantification: Rare event simulation and surrogate models

2017 - DKE Green - TU Braunschweig & TU Berlin - Germany


Slide showing Neural Network surrogate model performance

Discussing the use of Deep Neural Networks for time series prediction on a PDE model.

Deep networks in uncertainty quantification: Artificial Neural Networks and Machine Learning

2017 - DKE Green - TU Braunschweig & TU Berlin - Germany


Backpropagation in Artificial Neural Networks

Backpropagation in Artificial Neural Networks.

Probabilistic analysis in computational mechanics with applications in Civil Engineering

2016 - DKE Green - Postgraduate Research Symposium - University of New South Wales - Sydney, Australia


Uncertainty propagation diagram

Uncertainty propagation in numerical models.

Markov Chain Monte Carlo for Rare Event Reliability Analysis with Nonlinear Finite Elements

2016 - DKE Green - SIAM Conference on Uncertainty Quantification - EPFL - Lausanne, Switzerland


Plots of error bounds

Probabilistic prediction of rare events using Markov Chain Monte Carlo - discussing convergence of different simulation methods.