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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 ...

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 ...

Saksman's research deals with several mathematical problem areas that involve probabilistic questions in various setups. These include probabilistic methods in mathematical physics, analysis and ...

The design and construction of capital projects can be extremely complex. Uncertainty and risk add to this complexity and, as a result, many projects experience significant cost overruns and schedule ...

Probabilistic Safety Assessments (PSA), which was introduced in the 1970s as complement to deterministic safety analysis methods, is a well-established tool that supports design and safety assessment ...

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