Probabilistic machine learning

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 learning methods and their applications. The groups are led by professors Luigi Acerbi, Antti Honkela, Aapo Hyvärinen, Arto Klami, Mikko Koivisto, Kai Puolamäki, and Teemu Roos. 

Our research focuses on developing statistical machine learning techniques, approximate Bayesian inference, simulation-based inference, and methods for trustworthy machine learning, as well as exploring their practical implementation in domains such as medicine, physics and neuroscience. Check out our selected list of publications for examples of our recent work.

We are also part of the Finnish Center for Artificial Intelligence FCAI and the ELLIS Institute Finland, which promote collaboration and innovation in artificial intelligence research. You can find us at the Kumpula campus, and look below for news about our work and open positions.

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