Uncertainty in Complex Systems#
Welcome to the Uncertainty in Complex Systems lab website. At UICS, we develop probabilistic methods for understanding, predicting, and controlling complex dynamical systems. We are particularly interested in dealing with sparse, noisy, and indirect observations.
Research#
Our work uses Bayesian modelling and machine learning to identify the mechanisms by which complex systems evolve and behave.
Probabilistic modelling
Bayesian inference, model comparison, and nonparametric methods.
Complex & dynamic systems
(Dynamic) network analysis.
Efficient inference
Scalable approximate inference algorithms, such as Sequential Monte Carlo.
Applications
Neuroscience, developmental psychology, clinical genetics, and healthcare.
All stable processes we shall predict. All unstable processes we shall control.
—John von Neumann