Daniel Edward Pagendam

16 papers A* 1Journal 15
YearRankTypeTitle / Venue / Authors
2026 J jnl
Advancing integrated terrestrial nutrient budget modeling: Challenges and opportunities for improvement across space, time, and end-users.
Ecol. Informatics
Chiara Pasut, David I. Forrester, Thomas F. A. Bishop, Jacqueline R. England, Donald Gaydon, Peter Grace, Ian Harman, Sreekanth Janardhanan, Bennet Macdonald, Federico Maggi, Brendan P. Malone, Daniel Edward Pagendam, David W. Rassam, Dan F. Rosauer, Stephen H. Roxburgh, Ross D. Searle, Fiona H. M. Tang, Sabastine Ugbaje, Ying-Ping Wang, Jinyan Yang, Yingying Yu, Senani Karunaratne
2025 A* conf
Gaussian Ensemble Belief Propagation for Efficient Inference in High-Dimensional, Black-box Systems.
ICLR
Daniel MacKinlay, Russell Tsuchida, Daniel Edward Pagendam, Petra Kuhnert
2024 J jnl
Gaussian Ensemble Belief Propagation for Efficient Inference in High-Dimensional Systems.
CoRR
Daniel MacKinlay, Russell Tsuchida, Daniel Edward Pagendam, Petra Kuhnert
2023 J jnl
Exploiting Field Dependencies for Learning on Categorical Data.
CoRR
Zhibin Li, Piotr Koniusz, Lu Zhang, Daniel Edward Pagendam, Peyman Moghadam
2023 J jnl
Exploiting Field Dependencies for Learning on Categorical Data.
IEEE Trans. Pattern Anal. Mach. Intell.
Zhibin Li, Piotr Koniusz, Lu Zhang, Daniel Edward Pagendam, Peyman Moghadam
2023 J jnl
The effect of biologically mediated decay rates on modelling soil carbon sequestration in agricultural settings.
Environ. Model. Softw.
Mohammad-Javad Davoudabadi, Daniel Edward Pagendam, Christopher C. Drovandi, Jeff Baldock, Gentry White
2022 J jnl
Bayesian Neural Network Inference via Implicit Models and the Posterior Predictive Distribution.
CoRR
Joel Janek Dabrowski, Daniel Edward Pagendam
2022 J jnl
Bayesian Physics Informed Neural Networks for Data Assimilation and Spatio-Temporal Modelling of Wildfires.
CoRR
Joel Janek Dabrowski, Daniel Edward Pagendam, James Hilton, Conrad Sanderson, Daniel MacKinlay, Carolyn Huston, Andrew Bolt, Petra Kuhnert
2021 J jnl
A Semiautomatic Method for History Matching Using Sequential Monte Carlo.
SIAM/ASA J. Uncertain. Quantification
Christopher C. Drovandi, David J. Nott, Daniel Edward Pagendam
2021 J jnl
Advanced Bayesian approaches for state-space models with a case study on soil carbon sequestration.
Environ. Model. Softw.
Mohammad-Javad Davoudabadi, Daniel Edward Pagendam, Christopher C. Drovandi, Jeff Baldock, Gentry White
2021 J jnl
Gaussian process machine learning and Kriging for groundwater salinity interpolation.
Environ. Model. Softw.
Tao Cui, Daniel Edward Pagendam, Mat Gilfedder
2021 J jnl
Opportunistic Emulation of Computationally Expensive Simulations via Deep Learning.
CoRR
Conrad Sanderson, Daniel Edward Pagendam, Brendan Power, Frederick Bennett, Ross Darnell
2020 J jnl
Enforcing mean reversion in state space models for prawn pond water quality forecasting.
Comput. Electron. Agric.
Joel Janek Dabrowski, Ashfaqur Rahman, Daniel Edward Pagendam, Andrew George
2018 J jnl
Determining the initial spatial extent of an environmental impact assessment with a probabilistic screening methodology.
Environ. Model. Softw.
Luk Peeters, Daniel Edward Pagendam, Russell S. Crosbie, Praveen K. Rachakonda, Warrick R. Dawes, Lei Gao, Steve P. Marvanek, Yongqiang Zhang, Tim R. McVicar
2015 J jnl
Streamflow rating uncertainty: Characterisation and impacts on model calibration and performance.
Environ. Model. Softw.
Jorge L. Peña-Arancibia, Yongqiang Zhang, Daniel Edward Pagendam, Neil R. Viney, Julien Lerat, Albert I. J. M. van Dijk, Jai Vaze, Andrew J. Frost
2008 J jnl
Conceptualisation and application of models for groundwater-surface water interactions and nitrate attenuation potential in riparian zones.
Environ. Model. Softw.
David W. Rassam, Daniel Edward Pagendam, H. M. Hunter