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Publications

Browse the latest publications discussing the VIEWS early-warning system and results from related research projects

Working Paper

2024

The Impacts of Armed Conflict on Human Development: a Review of the Literature

Vesco et al. (2024)
Working Paper

2024

The Echoes of War: Persistent Effects of War on Health Outcomes

Rakhmankulova et al. (2024)
Working Paper

2024

Predicting Fatalities with Pre-trained Temporal Transformers: A Time Series Regression Approach

Macis et al. (2024)

Topics: Conflict forecasting, VIEWS Prediction Challenge 2023/2024
Working Paper

2024

Random Forest Predictions with Dyad Features

Gleditsch et al. (2024)

Topics: VIEWS Prediction Challenge 2023/2024
Working Paper

2024

Taking time seriously: Predicting conflict fatalities using temporal fusion transformers

Walterskirchen et al. (2024)

Topics: VIEWS Prediction Challenge 2023/2024
Peer-Reviewed Article

2024

Could vote buying be socially desirable? Exploratory analyses of a ‘failed’ list experiment

Hatz et al. (2024)

Topics: List experiment, Measurement, Social desirability bias, Vote buying
Working Paper

2024

Probabilistic Forecasting of Conflict Fatalities: Historical Quantiles vs. Bayesian Penalized Regression

Drauz & Becker (2024)

Topics: Conflict forecasting, VIEWS Prediction Challenge 2023/2024
Working Paper

2024

Forecasting Monthly Fatalities via a Negative Binomial Distribution and Comparison with a Hurdle Model and Neural Networks

Bodentien & Rüter (2024)

Topics: VIEWS Prediction Challenge 2023/2024
Working Paper

2024

Predicting uncertainty in stages: Using a semiparametric hierarchical hurdle model for predicting distributions of conflict fatalities

Fritz et al. (2024)

Topics: VIEWS Prediction Challenge 2023/2024
Working Paper

2024

Bayesian Density Forecasts for VIEWS

Patrick T. Brandt (2024)

Topics: VIEWS Prediction Challenge 2023/2024
Working Paper

2024

Predicting fatalities using newspaper text

Málaga et al. (2024)

Topics: VIEWS Prediction Challenge 2023/2024
Working Paper

2024

Forests of UncertainT(r)ees: Using tree-based ensembles to estimate probability distributions of future conflict

Mittermaier et al. (2024)

Topics: VIEWS Prediction Challenge 2023/2024
Working Paper

2024

A Zero-Inflated Poisson Generalized Additive Model for Forecasting Conflict Fatalities

Muchlinski & Thornhill (2024)

Topics: VIEWS Prediction Challenge 2023/2024
Working Paper

2024

Probabilistic Conflict Forecasting with Automated Machine Learning

D’Orazio (2024)

Topics: VIEWS Prediction Challenge 2023/2024
Working Paper

2024

Forecasting fatalities from state based conflicts using Markov models

Randahl & Vegelius (2024)

Topics: VIEWS Prediction Challenge 2023/2024
Working Paper

2024

Temporal patterns in conflict prediction: An improved shape-based approach

Schincariol et al. (2024)

Topics: VIEWS Prediction Challenge 2023/2024
Peer-Reviewed Article

2024

Integrating socio-hydrology, and peace and conflict research

Döring et al. (2024)

Topics: Peace and conflict research, Review, Socio-hydrology, Water governance
Model Documentation

2024

Models in VIEWS, version Fatalities002

Hegre et al. (2024)

Topics: fatalities002
Working Paper

2024

Building Resilience: The Effects of Conflict and Drought Parental Investments and Early Childhood Development

Nordenving & Rogall (2024)
Working Paper

2024

Women’s Empowerment and Post-Conflict Recovery after Mass Killings

Nordenving et al. (2024)

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The Violence & Impacts Early-Warning System (VIEWS) is an open-source project leveraging machine learning to predict armed conflict and its adverse impacts on humanitarian outcomes.

Supported by a global network of leading researchers, our research and state-of-the-art early-warning system helps governments and humanitarian actors take timely action to prevent or reduce the devastating effects of armed conflicts on affected communities.

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