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 98 of 99
1989
Inductive knowledge acquisition and induction methodologies
W Buntine
Knowledge-Based Systems 2 (1), 52-61, 1989
Research10 citationsKey Centre for Advanced Computing Sciences University of Technology, Sydney Broadway, 2007, Australia
W Buntine
Proceedings of the Sixth International Workshop on Machine Learning, Cornell …, 1989
Research
1988
Machine invention of first-order predicates by inverting resolution
S Muggleton, W Buntine
Machine Learning Proceedings 1988, 339-352, 1988
Research810 citationsGeneralized subsumption and its applications to induction and redundancy
W Buntine
Artificial intelligence 36 (2), 149-176, 1988
Research352 citationsInteractive induction
W Buntine, D Stirling
Proceedings. The Fourth Conference on Artificial Intelligence Applications …, 1988
Research52 citationsProcess routings in a steel mill: a challenging induction problem
D Stirling, W Buntine
Artificial Intelligence Developments and Applications, 301-313, 1988
Research19 citationsTowards constructive induction in first-order predicate calculus
SH Muggleton, W Buntine
Turing Institute, 1988
Research15 citationsSTEPHEN MUGGLETON (STEVE@ TURING. AC. UK)
W BUNTINE
Proceedings of the Fifth International Conference on Machine Learning: June …, 1988
Research
1987
Induction of Horn clauses: Methods and the plausible generalization algorithm
W Buntine
International Journal of Man-Machine Studies 26 (4), 499-519, 1987
Research30 citationsGOLD: an expert system for mineral Identification from reflectance spectra
R Lister, K Ali, C Horsfall, R Buda, W Buntine
Australian Joint Artificial Intelligence Conference, 29-43, 1987
Research8 citations- Machine Learning2 citations
Affiliation: NSW Institute of Technology and Macquarie University
W Buntine
Proceedings: Third Workshop on Uncertainty in Artificial Intelligence, July …, 1987
Research
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“Forecasting for Data Scientists”, a free 30-chapter video course by co-founder Dr Christoph Bergmeir, from fundamentals to advanced deep learning.