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 ...

What Is A Probabilistic Model? A probabilistic model is a statistical tool that accounts for randomness or uncertainty when predicting future events. Instead of giving a definitive answer, it ...

Accurately tracking atmospheric greenhouse gases requires not only fast predictions but also reliable estimates of ...

The local volatility model is widely used for pricing and hedging financial derivatives. While its main appeal is its capability of reproducing any given surface of observed option prices – it ...

WEST LAFAYETTE, Ind. — “You see, nature is unpredictable. How do you expect to predict it with a computer?” said American physicist Richard Feynman before computer scientists at a conference in 1981.

Storage, computation, and communication are the three pillars of modern information technology, with computation being the central aspect. The von Neumann architecture, based on the Turing machine ...

The rise of artificial intelligence (AI) and machine learning (ML) has created a crisis in computing and a significant need for more hardware that is both energy-efficient and scalable. A key step in ...

Probabilistic methods are increasingly being used to complement deterministic methods in assessing the safety and ensuring the reliability of research reactors. Addressing features specific to ...

Imagine a world where your computer doesn’t just work harder but smarter, tapping into the very chaos that surrounds us. It’s not science fiction—it’s the dawn of probabilistic and thermodynamic ...