Don't miss the big stories. Like us on Facebook. BENNINGTON — The Tutorial Center will pilot a new evening education initiative, the “Working Learner” Program, at it's Bennington location beginning on ...

The Oklahoma Court of Criminal Appeals has unanimously affirmed the use of BulletProof, a probabilistic genotyping software program, in the assault and battery trial of Patrick Marquise Napoleon, who ...

We study machine learning formulations of inductive program synthesis; given input-output examples, we try to synthesize source code that maps inputs to corresponding outputs. Our aims are to develop ...

Probabilistic Programming is a way of defining probabilistic models by overloading the operations in standard programming language to have probabilistic meanings. The goal is to specify probabilistic ...

Probabilistic programming has emerged as a powerful paradigm that integrates uncertainty directly into computational models. By embedding probabilistic constructs into conventional programming ...

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

Abstract: Causal inference is an important field in data science and cognitive artificial intelligence. It requires the construction of complex probabilistic models to describe the causal ...

This tutorial will introduce a new paradigm for agent-based models (ABMs) that leverages automatic differentiation (AD) to efficiently compute simulator gradients. In particular, this tutorial will ...

Researchers have developed an easy-to-use tool that enables someone to perform complicated statistical analyses on tabular data using just a few keystrokes. Their method combines probabilistic AI ...

Some 230 million people in the United States face the potential of damaging earthquakes in 100 years, according to the latest U.S. National Seismic Hazard Model, or NSHM. That’s about 40 million more ...