Acknowledgements
We gratefully acknowledge contributions and public resources by collaborators whose work informs parts of this project. Any adaptations and errors remain our own.
Thomas Schincariol
- Public repositories and datasets supporting conflict‑fatality forecasting.
- Historical predictions and grid‑level resources used in parts of our pipelines.
- Selected repositories: Pace-map-risk (historical predictions), Live_3D_forecast (grid data feed)
Hannah Frank
- Research and methodological contributions relevant to forecasting and evaluation.
- Co‑authorship and collaboration on related scholarly work.
Selected Publications
Works with Schincariol
- Endogenous conflict and the limits of predictive optimizationChadefaux T & Schincariol T — EPJ Data Science (2025)
- The 2023/24 VIEWS Prediction challenge: Predicting the number of fatalities in armed conflict, with uncertaintyHegre H et al. (incl. Schincariol T, Frank H & Chadefaux T) — Journal of Peace Research (2025)
- Accounting for variability in conflict dynamics: A pattern-based predictive modelSchincariol T, Frank H & Chadefaux T — Journal of Peace Research (2025)
- Temporal Patterns in Migration Flows: Evidence from South SudanSchincariol T & Chadefaux T — Journal of Forecasting (2024)
Works with Frank
- The 2023/24 VIEWS Prediction challenge: Predicting the number of fatalities in armed conflict, with uncertaintyHegre H et al. (incl. Schincariol T, Frank H & Chadefaux T) — Journal of Peace Research (2025)
- Accounting for variability in conflict dynamics: A pattern-based predictive modelSchincariol T, Frank H & Chadefaux T — Journal of Peace Research (2025)
Acknowledgement does not imply endorsement. Public datasets and repositories referenced here are credited to their respective authors; any transformations applied for this site are the responsibility of the PaCE team.