Vizumap: an R package for visualising uncertainty in spatial data. - Lydia R. Lucchesi; Petra M. Kuhnert; Christopher K. Wikle (J. Open Source Softw., 2021)

Smallset Timelines: A Visual Representation of Data Preprocessing Decisions. - Lydia R. Lucchesi; Petra M. Kuhnert; Jenny L. Davis; Lexing Xie (FAccT, 2022)

A Spatio-Temporal Neural Network Forecasting Approach for Emulation of Firefront Models. - Andrew Bolt; Carolyn Huston; Petra Kuhnert; Joel Janek Dabrowski; James Hilton 001; Conrad Sanderson (SPA, 2022)

An Emulation Framework for Fire Front Spread. - Andrew Bolt; Joel Janek Dabrowski; Carolyn Huston; Petra Kuhnert (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)

Modelling Within-Season Variation in Light Use Efficiency Enhances Productivity Estimates for Cropland. - Michael J. Wellington; Petra M. Kuhnert; Luigi J. Renzullo; Roger A. Lawes (Remote. Sens., 2022)

A Neural Emulator for Uncertainty Estimation of Fire Propagation. - Andrew Bolt; Conrad Sanderson; Joel Janek Dabrowski; Carolyn Huston; Petra Kuhnert (INNS DLIA@IJCNN, 2023)

A framework for modelling spatio-temporal trends in crop production using generalised additive models. - Michael J. Wellington; Roger A. Lawes; Petra M. Kuhnert (Comput. Electron. Agric., 2023)

Resolving Ethics Trade-offs in Implementing Responsible AI. - Conrad Sanderson; Emma Schleiger; David Douglas; Petra Kuhnert; Qinghua Lu 001 (CoRR, 2024)

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)

Position: We need responsible, application-driven (RAD) AI research. - Sarah Hartman; Cheng Soon Ong; Julia Powles; Petra Kuhnert (CoRR, 2025)