The key idea behind the probabilistic framework to machine learning is that learning can be thought of as inferring plausible models to explain observed data. A machine can use such models to make ...

Industries from retail to finance are using clustering to personalize services, detect fraud, monitor equipment and improve ...

The Helsinki Probabilistic Machine Learning Lab encompasses seven research groups at the Department of Computer Science of the University of Helsinki, all specializing in probabilistic machine ...

The problem was reframed as a probabilistic classification ... Vasilis Michalakopoulos et al, A machine learning-based framework for clustering residential electricity load profiles to enhance ...

The second part of the module introduces and provides training in further topics of probabilistic machine learning such as Graphical models, mixtures and cluster analysis, Variational approximation, ...

We use probabilistic machine learning to look at the calibration problem in a probabilistic framework based on Gaussian processes. This immediately gives a way of encoding prior beliefs about the ...

The Department of Computer Science, Faculty of Science, University of Helsinki invites applications for a Postdoctoral Researcher in Probabilistic Machine Learning and Amortized Inference. The ...

Deep learning, for instance, is an example of a successful machine learning method loosely based on biological neural networks. We develop probabilistic modelling techniques to produce predictions for ...