What was the rationale behind applying machine learning (ML) models to improve identification probability in the absence of ...

The multiple condition (MC)-retention model is an uncertainty-aware graph-based neural network that predicts liquid chromatography (LC) retention times across multiple column chem ...

In the Artemis II mission, NASA will test out a pair of new solar radiation forecasts, developed at University of Michigan Engineering, designed to protect astronauts venturing away from Earth. The ...

Neural-network processors accelerate AI program execution while development tools help you get to market fast.

AI is no longer seen as a futuristic discipline but has emerged as a major focus area for business growth. It's predicted ...

Continuous analytics and automated monitoring are enabling insurers to respond faster to emerging performance shifts ...

Using six gut- and diet-derived metabolites, a machine learning model had 79% accuracy in classifying adults as having ...

Modality-agnostic decoders leverage modality-invariant representations in human subjects' brain activity to predict stimuli irrespective of their modality (image, text, mental imagery).

The Office of Undergraduate Research organizes the Symposium of Student Scholars twice per year, offering students a unique ...

Ahead of ElasticON London 2026, FinTech magazine met with Tim Brophy to discuss FSI challenges, Innovation and AI as a value ...

Government-funded academic research on parallel computing, stream processing, real-time shading languages, and programmable ...