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 ...

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 ...

The Department of Computer Science, Faculty of Science, University of Helsinki invites applications for a Postdoctoral Researcher in Probabilistic Machine Learning and Amortized Inference. The ...

One virtue of probabilistic models is that they straddle the gap between cognitive science, artificial intelligence, and machine learning. The same methodology is useful for both understanding the ...

Artificial Intelligence (AI), Machine Learning, and Deep Learning are all topics of considerable interest in news articles and industry discussions these days. However, to the average person or to ...

We use probabilistic machine learning to look at the calibration problem in a probabilistic framework based on Gaussian processes. This immediately gives a way of encoding prior beliefs about the ...

The most widely covered topics were machine learning and probabilistic learning, neural networks, and computer vision. AI research in different countries focused on different fields, with papers ...

Machine learning is a subset of AI that focuses on building systems capable of learning from data, identifying patterns, and making decisions with minimal human intervention. These systems improve ...