Hans Salomonsson

Forskningsingenjör at CSE Verksamhetsstöd

I am passionate about all aspects of machine learning and its dramatic implications for business strategy and society. I have during my career in industry and academia implemented, applied and improved many types of machine learning algorithms. I enjoy taking state of the art machine learning research and adapting it to solve particular research and business problems.

Source: orcid.org
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Showing 6 publications


Bayesian optimization in ab initio nuclear physics

Andreas Ekström, Christian Forssen, Christos Dimitrakakis et al
Journal of Physics G: Nuclear and Particle Physics. Vol. 46 (9)
Journal article

A data-driven algorithm to predict throughput bottlenecks in a production system based on active periods of the machines

Mukund Subramaniyan, Anders Skoogh, Hans Salomonsson et al
Computers and Industrial Engineering. Vol. 125, p. 533-544
Journal article

Data-driven algorithm for throughput bottleneck analysis of production systems

Mukund Subramaniyan, Anders Skoogh, Hans Salomonsson et al
Production and Manufacturing Research. Vol. 6 (1), p. 225-246
Journal article

An algorithm for data-driven shifting bottleneck detection

Mukund Subramaniyan, Anders Skoogh, Maheshwaran Gopalakrishnan et al
Cogent Engineering. Vol. 3 (1), p. 1-19
Journal article

Word Sense Disambiguation using a Bidirectional LSTM

Mikael Kågebäck, Hans Salomonsson
5th Workshop on Cognitive Aspects of the Lexicon (CogALex-V) at the 26th International Conference on Computational Linguistics (COLING 2016)
Paper in proceeding

Machine Learning to predict a ship's fuel consumption in seaways

Wengang Mao, Pär Brandholm, Peter Lenaers et al
13th International Symposium on Practical Design of Ships and Other Floating Structures, PRADS 2016; Hotel Crowne PlazaCopenhagen; Denmark; 4 September 2016 through 8 September 2016
Paper in proceeding

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