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 ...

The rapid advancement of spatial and single-cell omics technologies has revolutionized molecular biosciences by enabling high-resolution profiling of gene ...

As semiconductor technologies advance, device structures are becoming increasingly complex. New materials and architectures introduce intricate physical effects requiring accurate modeling to ensure ...

New integrations between Python and MATLAB’s Simulink platform are enabling engineers to coexecute Python models, automate VLSI workflows, and bridge AI-driven design with traditional simulation.

Adrian Macneil has a solid understanding of this space. As an executive at the self-driving startup Cruise, he built the ...

As the world grapples with the energy crisis and environmental concerns, the focus on renewable energy sources has intensified. Lithium-ion batteries, with their high energy density and low pollution, ...

Using generative AI to design, train, or perform steps within a machine-learning system is risky, argues computer scientist Micheal Lones in a paper appearing in Patterns. Though large language models ...

Real-world evidence (RWE) has become a crucial driver of the pharmaceutical and biotechnology industries in recent years. In fact, RWE is now included in 70 percent of new drug and biologic regulatory ...

The study, titled “Teach AI What It Doesn’t Know,” published in AI Magazine, presents a detailed research agenda by Sean Du of Nanyang Technological University, focused on building reliable machine ...