D. Warne

发表

Robust Simulation Design for Generalized Linear Models in Conditions of Heteroscedasticity or Correlation

Antony M. Overstall, Queensland University of Technology, U. Southampton, 2022, 2022 Winter Simulation Conference (WSC).

Using Experimental Data and Information Criteria to Guide Model Selection for Reaction–Diffusion Problems in Mathematical Biology

R. Baker, M. Simpson, D. Warne, 2019, Bulletin of Mathematical Biology.

Explainability of the COVID-19 epidemiological model with nonnegative tensor factorization

David J. Warne, K. Mengersen, R. Nayak, 2022, International journal of data science and analytics.

Multifidelity multilevel Monte Carlo to accelerate approximate Bayesian parameter inference for partially observed stochastic processes

David J. Warne, Thomas P. Prescott, Alan Turing Institute, 2021, J. Comput. Phys..

Bayesian score calibration for approximate models

Joshua J. Bon, D. Nott, C. Drovandi, 2022, 2211.05357.

Bayesian uncertainty quantification to identify population level vaccine hesitancy behaviours

C. Drovandi, A. Jenner, A. Browning, 2022, medRxiv.

Misspecification-robust Sequential Neural Likelihood

David T. Frazier, D. Nott, C. Drovandi, 2023, ArXiv.

Simulation and inference algorithms for stochastic biochemical reaction networks: from basic concepts to state-of-the-art

Matthew J Simpson, Ruth E Baker, David J Warne, 2018, Journal of the Royal Society Interface.

Hindsight is 2020 vision: a characterisation of the global response to the COVID-19 pandemic

David J. Warne, K. Mengersen, A. Mira, 2020, BMC Public Health.

Utility of genetic algorithms for solving large scale construction time/cost trade-off problems

Forrest J. Masters, David J. Warne, Duzgun Agdas, 2018 .

Accelerating computational Bayesian inference for stochastic biochemical reaction network models using multilevel Monte Carlo sampling

Ruth E. Baker, Matthew J. Simpson, David J. Warne, 2016, bioRxiv.

Vector Operations for Accelerating Expensive Bayesian Computations – A Tutorial Guide

Scott A. Sisson, David J. Warne, Christopher Drovandi Queensland University of Technology, 2019, Bayesian Analysis.

Acceleration of expensive computations in Bayesian statistics using vector operations pdf

Christopher C. Drovandi, Scott A. Sisson, David J. Warne, 2019, ArXiv.

Rapid Bayesian Inference for Expensive Stochastic Models

David J. Warne, R. Baker, M. Simpson, 2019, J. Comput. Graph. Stat..

Parameter identifiability and model selection for sigmoid population growth models.

R. Baker, M. Simpson, A. Browning, 2021, Journal of theoretical biology.

Parameter identifiability and model selection for sigmoid population growth models

R. Baker, M. Simpson, A. Browning, 2021, bioRxiv.

An Eﬃcient Algorithm for the Detection of Eden

David J. Warne, D. Warne, 2017 .

Identifiability analysis for stochastic differential equation models in systems biology

Kevin Burrage, Matthew J Simpson, Ruth E Baker, 2020, bioRxiv.

Generalised likelihood profiles for models with intractable likelihoods

Oliver J. Maclaren, O. Maclaren, M. J. Simpson, 2023, Statistics and Computing.

Bayesian score calibration for approximate models

Joshua J. Bon, D. Nott, C. Drovandi, 2022, 2211.05357.

Computationally efficient framework for diagnosing, understanding and predicting biphasic population growth

David J. Warne, Oliver J. Maclaren, R. J. Murphy, 2022, bioRxiv.

A practical guide to pseudo-marginal methods for computational inference in systems biology.

R. Baker, M. Simpson, D. Warne, 2019, Journal of theoretical biology.

Using Experimental Data and Information Criteria to Guide Model Selection for Reaction–Diffusion Problems in Mathematical Biology

Matthew J Simpson, Ruth E Baker, David J Warne, 2018, bioRxiv.

Calibration of Agent Based Models for Monophasic and Biphasic Tumour Growth using Approximate Bayesian Computation

C. Drovandi, A. Jenner, Roberto Salomone, 2023, bioRxiv.

Optimal Quantification of Contact Inhibition in Cell Populations.

Matthew J Simpson, Ruth E Baker, David J Warne, 2017, Biophysical journal.

Multilevel rejection sampling for approximate Bayesian computation

Ruth E. Baker, Matthew J. Simpson, David J. Warne, 2017, Comput. Stat. Data Anal..

An Efficient Algorithm for the Detection of Eden

Ross Hayward, David J. Warne, Neil Kelson, 2013, Complex Syst..

Bayesian score calibration for approximate models

Joshua J. Bon, D. Nott, C. Drovandi, 2022, 2211.05357.

Efficient multifidelity likelihood-free Bayesian inference with adaptive computational resource allocation

Ruth E Baker, David J Warne, Thomas P. Prescott, 2021, Journal of Computational Physics.

Using Experimental Data and Information Criteria to Guide Model Selection for Reaction–Diffusion Problems in Mathematical Biology

Ruth E. Baker, Matthew J. Simpson, David J. Warne, 2018, Bulletin of Mathematical Biology.

Image-based flow visualisation (IBFV) to enhance interpretation of complex flow patterns within a shallow tidal barrier estuary

David J. Warne, Genevieve Larsen, Joseph Young, 2013, Environ. Model. Softw..

Implementation of parallel tridiagonal solvers for a heterogeneous computing environment

Jasmine Banks, Neil A. Kelson, David J. Warne, 2016 .

Solving Tri-Diagonal Linear Systems using Field Programmable Gate Arrays

Neil A. Kelson, Ross F. Hayward, David J. Warne, 2012, HiPC 2012.