On Friday the 28th of October 2022, M.Sc. Tommi Mäklin defends his doctoral thesis on Probabilistic Methods for High-Resolution Metagenomics. The thesis is related to research done in the Department ...

For humans and machines, intelligence requires making sense of the world — inferring simple explanations for the mishmosh of information coming in through our senses, discovering regularities and ...

That’s because a new framework is improving the probabilistic reasoning of LLMS like ChatGPT and Gemini. School of ...

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 ...

Probabilistic graphical models are a powerful technique for handling uncertainty in machine learning. The course will cover how probability distributions can be represented in graphical models, how ...

The study shows how probabilistic clustering supports intelligent data transmission strategies. The authors propose leveraging cluster probabilities to define transmission rules: sensors with a high ...

The phenomenal success of our integrated circuits managed to obscure an awkward fact: they're not always the best way to solve problems. The features of modern computers—binary operations, separated ...

*Note: This course description is only applicable for the Computer Science Post-Baccalaureate program. Additionally, students must always refer to course syllabus for the most up to date information.

In the event of dry weather and high winds, power system-ignited incidents are more likely to develop into wildfires. The risk is greater if vegetation is nearby. A new study provides the methodology ...