In an interview with Technology Networks, Dr. Daniel Reker discusses how machine learning is improving data-scarce areas of ...

This paper presents a novel framework for optimizing Carbon Release (CR) through an AI-driven approach to Fossil Fuel Intake (FFI) management. We propose a new training methodology for AI models to ...

Neel Somani has built a career that sits at the intersection of theory and practice. His work spans formal methods, mac ...

Investments in automation and additional tools for data analytics keep coming to packaging lines as plants become more connected. Machine learning and digital twin technology are increasing throughput ...

What if vaccine development didn’t have to take a decade? This piece looks at how AI is helping scientists ask better ...

A new peer-reviewed study published in the journal Algorithms signals a major shift in how humanitarian logistics can be ...

The new toolkit integrates with Keysight’s device modeling software to automate parameter extraction and shorten compact-model and PDK development cycles.

Are Machine Learning (ML) algorithms superior to traditional econometric models for GDP nowcasting in a time series setting? Based on our evaluation of all models from both classes ever used in ...

As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models designed to process graph-structured data. Currently, GNNs are effective ...