Most algorithms in order restricted statistical inference express the estimates in terms of certain summary statistics computed from pooled samples. These algorithms may or may not yield optimal ...

The Virtual Brain Inference (VBI) toolkit enables efficient, accurate, and scalable Bayesian inference over whole-brain network models, improving parameter estimation, uncertainty quantification, and ...

AI inference uses trained data to enable models to make deductions and decisions. Effective AI inference results in quicker and more accurate model responses. Evaluating AI inference focuses on speed, ...

Deep learning, probably the most advanced and challenging foundation of artificial intelligence (AI), is having a significant impact and influence on many applications, enabling products to behave ...

AI inference at the edge refers to running trained machine learning (ML) models closer to end users when compared to traditional cloud AI inference. Edge inference accelerates the response time of ML ...