WASP Machine learning

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The Division of Statistics and Machine Learning develops the machine learning methods that autonomous systems use when learning from data. Our research and education focuses on probabilistic modeling and efficient algorithms for learning, prediction and decision making under uncertainty.

The researchers at The Division of Statistics and Machine Learning, STIMA, are active in both basic machine learning methodology as well as in applied industrial research in areas such as transport systems, telecommunication, robotics, autonomous vehicles, medical technology, climate modeling, and software development.

The research at the division has resulted in efficient simulation-based inference algorithms for large scale data, new graphical models for describing structure and dependencies in complex data, methods for analyzing causal relationships, and other contributions to the machine learning area.

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WASP machine learning

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