Articulate the primary interpretations of probability theory and the role these interpretations play in Bayesian inference Use Bayesian inference to solve real-world statistics and data science ...

Despite major methodological developments, Bayesian inference in Gaussian graphical models remains challenging in high dimension due to the tremendous size of the model space. This article proposes a ...

Compute-in-memory (CIM) is not necessarily an Artificial Intelligence (AI) solution; rather, it is a memory management solution. CIM could bring advantages to AI processing by speeding up the ...

The CNCF is bullish about cloud-native computing working hand in glove with AI. AI inference is the technology that will make hundreds of billions for cloud-native companies. New kinds of AI-first ...

What is the neuropsychological basis for the brain's ever-changing contextualized goals? I explore this question from the perspective of the Affect Management Framework (AMF).

Ambitious artificial intelligence computing startup Cerebras Systems Inc. is raising the stakes in its battle against Nvidia Corp., launching what it says is the world’s fastest AI inference service, ...

This course introduces the theoretical, philosophical, and mathematical foundations of Bayesian Statistical inference. Students will learn to apply this foundational knowledge to real-world data ...