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 programming languages (PPLs) have emerged as a transformative tool for expressing complex statistical models and automating inference procedures. By integrating probability theory into ...

Researchers can demonstrate that on some standard computer-vision tasks, short programs -- less than 50 lines long -- written in a probabilistic programming language are competitive with conventional ...

When you’re programming an artificial intelligence application, you’re usually building statistical models that output discrete values. Is that image a human face? Whose face is it? Is that face ...

Thomas Dullien discusses how language design choices impact performance, how Google's monorepo culture and Amazon's two-pizza-team culture impact code efficiency, and why statistical variance is an ...

An app developed by Gamalon recognizes objects after seeing a few examples. A learning program recognizes simpler concepts such as lines and rectangles. Machine learning is becoming extremely powerful ...

Scientists have built simulations to help explain behavior in the real world, including modeling for disease transmission and prevention, autonomous vehicles, climate science, and in the search for ...

COPENHAGEN, Denmark, June 25, 2021 (GLOBE NEWSWIRE) -- Evaxion Biotech A/S (Nasdaq: EVAX), a clinical-stage biotechnology company specializing in the development of AI-driven immunotherapies to ...