Bayesian inference
Bayesian inference is a method of statistical inference in which Bayes' theorem is used to update the probability for a hypothesis as more evidenceor information becomes available (Wikipedia).
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| Name | Expertise |
|---|---|
| Optimisation, Machine learning, Bayesian inference, Statistical modelling, Frequentist inference | |
| Saptarshi Das | Optimisation, Physical Modelling, Machine Learning, Bayesian Inference, Time Series Analysis, Statistical Modelling, Emulation/Uncertainty Quantification, Frequentist Inference, High Performance Computing, Signal Processing, Control Systems, Image Processing |
| Samuel Engle | Causality, Bayesian Inference, Statistical Modelling, Frequentist Inference, Decision Theory |
| Raphaëlle Haywood | Physical Modelling, Machine Learning, Bayesian Inference, Time Series Analysis |
| Bernard Nortier | Optimisation, Machine learning, Bayesian inference, Time series analysis, Statistical modelling, Emulation / uncertainty quantification, Frequentist inference |
| David Richards | Optimisation, Causality, Physical Modelling, Software Engineering, Machine Learning, Bayesian Inference, Time Series Analysis, Frequentist Inference, High Performance Computing, Statistical Modelling |
| Tj McKinley | Bayesian inference, Statistical modelling |
| Stefan Siegert | Spatial statistics, Physical modelling, Software engineering, Machine learning, Bayesian inference, Time series analysis, Statistical modelling, Emulation / uncertainty quantification, Frequentist inference |
| Danny Williamson | Decision theory, Optimisation, Machine learning, Bayesian inference, Statistical modelling, Emulation / uncertainty quantification |
