Conceptualisation and application of models for groundwater-surface water interactions and nitrate attenuation potential in riparian zones. - David W. Rassam; Daniel Edward Pagendam; H. M. Hunter (Environ. Model. Softw., 2008)

Streamflow rating uncertainty: Characterisation and impacts on model calibration and performance. - Jorge L. Peña-Arancibia; Yongqiang Zhang 004; Daniel Edward Pagendam; Neil R. Viney; Julien Lerat; Albert I. J. M. van Dijk; Jai Vaze; Andrew J. Frost (Environ. Model. Softw., 2015)

Determining the initial spatial extent of an environmental impact assessment with a probabilistic screening methodology. - Luk Peeters; Daniel Edward Pagendam; Russell S. Crosbie; Praveen K. Rachakonda; Warrick R. Dawes; Lei Gao 002; Steve P. Marvanek; Yongqiang Zhang 004; Tim R. McVicar (Environ. Model. Softw., 2018)

Enforcing mean reversion in state space models for prawn pond water quality forecasting. - Joel Janek Dabrowski; Ashfaqur Rahman; Daniel Edward Pagendam; Andrew George (Comput. Electron. Agric., 2020)

Opportunistic Emulation of Computationally Expensive Simulations via Deep Learning. - Conrad Sanderson; Daniel Edward Pagendam; Brendan Power; Frederick Bennett; Ross Darnell (CoRR, 2021)

Gaussian process machine learning and Kriging for groundwater salinity interpolation. - Tao Cui; Daniel Edward Pagendam; Mat Gilfedder (Environ. Model. Softw., 2021)

Advanced Bayesian approaches for state-space models with a case study on soil carbon sequestration. - Mohammad-Javad Davoudabadi; Daniel Edward Pagendam; Christopher C. Drovandi; Jeff Baldock; Gentry White (Environ. Model. Softw., 2021)

A Semiautomatic Method for History Matching Using Sequential Monte Carlo. - Christopher C. Drovandi; David J. Nott; Daniel Edward Pagendam (SIAM/ASA J. Uncertain. Quantification, 2021)

Bayesian Neural Network Inference via Implicit Models and the Posterior Predictive Distribution. - Joel Janek Dabrowski; Daniel Edward Pagendam (CoRR, 2022)

Bayesian Physics Informed Neural Networks for Data Assimilation and Spatio-Temporal Modelling of Wildfires. - Joel Janek Dabrowski; Daniel Edward Pagendam; James Hilton 001; Conrad Sanderson; Daniel MacKinlay; Carolyn Huston; Andrew Bolt; Petra Kuhnert (CoRR, 2022)

The effect of biologically mediated decay rates on modelling soil carbon sequestration in agricultural settings. - Mohammad-Javad Davoudabadi; Daniel Edward Pagendam; Christopher C. Drovandi; Jeff Baldock; Gentry White (Environ. Model. Softw., 2023)

Exploiting Field Dependencies for Learning on Categorical Data. - Zhibin Li 002; Piotr Koniusz; Lu Zhang 062; Daniel Edward Pagendam; Peyman Moghadam (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

Gaussian Ensemble Belief Propagation for Efficient Inference in High-Dimensional Systems. - Daniel MacKinlay; Russell Tsuchida; Daniel Edward Pagendam; Petra Kuhnert (CoRR, 2024)

Gaussian Ensemble Belief Propagation for Efficient Inference in High-Dimensional, Black-box Systems. - Daniel MacKinlay; Russell Tsuchida; Daniel Edward Pagendam; Petra Kuhnert (ICLR, 2025)