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ORCIDDaniel Edward Pagendam
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2020 – today
- 2024
[i5]Daniel MacKinlay, Russell Tsuchida, Daniel Edward Pagendam, Petra Kuhnert:
Gaussian Ensemble Belief Propagation for Efficient Inference in High-Dimensional Systems. CoRR abs/2402.08193 (2024)- 2023
- [j9]Mohammad-Javad Davoudabadi
, Daniel Edward Pagendam, Christopher C. Drovandi, Jeff Baldock, Gentry White:
The effect of biologically mediated decay rates on modelling soil carbon sequestration in agricultural settings. Environ. Model. Softw. 168: 105786 (2023) - [j8]Zhibin Li, Piotr Koniusz, Lu Zhang, Daniel Edward Pagendam, Peyman Moghadam:
Exploiting Field Dependencies for Learning on Categorical Data. IEEE Trans. Pattern Anal. Mach. Intell. 45(11): 13509-13522 (2023) - [i4]Zhibin Li, Piotr Koniusz, Lu Zhang, Daniel Edward Pagendam, Peyman Moghadam:
Exploiting Field Dependencies for Learning on Categorical Data. CoRR abs/2307.09321 (2023) - 2022
- [i3]Joel Janek Dabrowski, Daniel Edward Pagendam:
Bayesian Neural Network Inference via Implicit Models and the Posterior Predictive Distribution. CoRR abs/2209.02188 (2022) - [i2]Joel Janek Dabrowski, Daniel Edward Pagendam, James Hilton, Conrad Sanderson, Daniel MacKinlay, Carolyn Huston, Andrew Bolt, Petra Kuhnert:
Bayesian Physics Informed Neural Networks for Data Assimilation and Spatio-Temporal Modelling of Wildfires. CoRR abs/2212.00970 (2022) - 2021
- [j7]Mohammad-Javad Davoudabadi, Daniel Edward Pagendam, Christopher C. Drovandi, Jeff Baldock, Gentry White:
Advanced Bayesian approaches for state-space models with a case study on soil carbon sequestration. Environ. Model. Softw. 136: 104919 (2021) - [j6]Tao Cui, Daniel Edward Pagendam, Mat Gilfedder:
Gaussian process machine learning and Kriging for groundwater salinity interpolation. Environ. Model. Softw. 144: 105170 (2021) - [j5]Christopher C. Drovandi, David J. Nott, Daniel Edward Pagendam:
A Semiautomatic Method for History Matching Using Sequential Monte Carlo. SIAM/ASA J. Uncertain. Quantification 9(3): 1034-1063 (2021) - [i1]Conrad Sanderson, Daniel Edward Pagendam, Brendan Power, Frederick Bennett, Ross Darnell:
Opportunistic Emulation of Computationally Expensive Simulations via Deep Learning. CoRR abs/2108.11057 (2021) - 2020
- [j4]Joel Janek Dabrowski, Ashfaqur Rahman, Daniel Edward Pagendam, Andrew George:
Enforcing mean reversion in state space models for prawn pond water quality forecasting. Comput. Electron. Agric. 168 (2020)
2010 – 2019
- 2018
- [j3]Luk Peeters, Daniel Edward Pagendam, Russell S. Crosbie, Praveen K. Rachakonda, Warrick R. Dawes, Lei Gao, Steve P. Marvanek, Yongqiang Zhang, Tim R. McVicar:
Determining the initial spatial extent of an environmental impact assessment with a probabilistic screening methodology. Environ. Model. Softw. 109: 353-367 (2018) - 2015
- [j2]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:
Streamflow rating uncertainty: Characterisation and impacts on model calibration and performance. Environ. Model. Softw. 63: 32-44 (2015)
2000 – 2009
- 2008
- [j1]David W. Rassam, Daniel Edward Pagendam, H. M. Hunter:
Conceptualisation and application of models for groundwater-surface water interactions and nitrate attenuation potential in riparian zones. Environ. Model. Softw. 23(7): 859-875 (2008)
Coauthor Index
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