Research & Decision Science
Where forecasting research becomes operational decision infrastructure
RabbitHawk is built on peer-reviewed work in probabilistic forecasting, hierarchical reconciliation, optimization and applied AI, translated into systems that improve real decisions under real constraints.
- publications
- 1,181publications
- citations
- 53,485citations
- highly cited papers
- Top 1%highly cited papers
Scientific foundations
Methods proven in the literature, applied in production
Our team’s research is recognized at the field’s leading venues and used at scale by major organizations. We bring that rigor to enterprise planning, but judge every method by whether it improves decisions in practical settings.
Research → product
| Research area | Enterprise problem | RabbitHawk capability |
|---|---|---|
| Hierarchical forecasting | Local plans do not add up to executive targets | Reconciled forecasts across every level |
| Probabilistic forecasting | Point forecasts hide risk | Full predictive distributions, intervals and scenario ranges |
| Optimization | Forecasts do not tell teams what to do | Constraint-aware recommendations |
| Agentic AI | Context is trapped in emails and notes | Context ingestion and decision agents |
| Human-in-the-loop AI | Automation without trust creates resistance | Approval, override and audit trails |
| Alignment science | Teams optimize against conflicting goals | 90North alignment and goal clarity |
Hierarchical forecasting
Local plans do not add up to executive targets
Reconciled forecasts across every level
Probabilistic forecasting
Point forecasts hide risk
Full predictive distributions, intervals and scenario ranges
Optimization
Forecasts do not tell teams what to do
Constraint-aware recommendations
Agentic AI
Context is trapped in emails and notes
Context ingestion and decision agents
Human-in-the-loop AI
Automation without trust creates resistance
Approval, override and audit trails
Alignment science
Teams optimize against conflicting goals
90North alignment and goal clarity
Selected publications
The full peer-reviewed database: search by title, author, venue, category or year.
1,181 results · page 35 of 99
2018
A note on the validity of cross-validation for evaluating autoregressive time series prediction
C Bergmeir, RJ Hyndman, B Koo
Computational Statistics & Data Analysis 120, 70-83, 2018
Forecasting887 citationsExploring the sources of uncertainty: Why does bagging for time series forecasting work?
F Petropoulos, RJ Hyndman, C Bergmeir
European Journal of Operational Research 268 (2), 545-554, 2018
Machine Learning211 citationsCharacterising risk of in-hospital mortality following cardiac arrest using machine learning: A retrospective international registry study
S Nanayakkara, S Fogarty, M Tremeer, K Ross, B Richards, C Bergmeir, ...
PLoS medicine 15 (11), e1002709, 2018
Machine Learning145 citationsLearning how to actively learn: A deep imitation learning approach
M Liu, W Buntine, G Haffari
Proceedings of the 56th Annual Meeting of the Association for Computational …, 2018
Research115 citationsAdaptive knowledge sharing in multi-task learning: Improving low-resource neural machine translation
P Zaremoodi, W Buntine, G Haffari
Annual Meeting of the Association of Computational Linguistics 2018, 656-661, 2018
Machine Learning75 citationsPackage ‘Mcomp’
R Hyndman, M Akram, C Bergmeir, M O'Hara-Wild, MR Hyndman
Research64 citationsLearning to actively learn neural machine translation
M Liu, W Buntine, G Haffari
Conference on Natural Language Learning 2018, 334-344, 2018
Machine Learning60 citationsSolution-based phase saving for CP: A value-selection heuristic to simulate local search behavior in complete solvers
E Demirović, G Chu, PJ Stuckey
International Conference on Principles and Practice of Constraint …, 2018
Optimization55 citationsChuffed, a lazy clause generation solver
G Chu, PJ Stuckey, A Schutt, T Ehlers, G Gange, K Francis
URL: https://github. com/chuffed/chuffed, 2018
Research51 citationsMixed-integer linear programming and constraint programming formulations for solving resource availability cost problems
S Kreter, A Schutt, PJ Stuckey, J Zimmermann
European Journal of Operational Research 266 (2), 472-486, 2018
Machine Learning49 citationsDirichlet belief networks for topic structure learning
H Zhao, L Du, W Buntine, M Zhou
Advances in neural information processing systems 31, 2018
Research46 citationsMachine learning and constraint programming for relational-to-ontology schema mapping
D De Uña, N Rümmele, G Gange, P Schachte, PJ Stuckey
International Joint Conference on Artificial Intelligence 2018, 1277-1283, 2018
Machine Learning36 citations
Learn the science behind the engine
“Forecasting for Data Scientists”, a free 30-chapter video course by co-founder Dr Christoph Bergmeir, from fundamentals to advanced deep learning.