Accurately tracking atmospheric greenhouse gases requires not only fast predictions but also reliable estimates of ...

Deep learning is increasingly used in financial modeling, but its lack of transparency raises risks. Using the well-known Heston option pricing model as a benchmark, researchers show that global ...

Researchers have used machine learning to create a model that simulates reactive processes in organic materials and conditions. Researchers from Carnegie Mellon University and Los Alamos National ...

In a breakthrough for artificial intelligence (AI) and finance, computer scientists from Texas A&M University have developed a machine learning based method called Symbolic Modeling to handle ...

The semiconductor industry is entering an era of unprecedented complexity, driven by advanced architectures such as Gate-All-Around (GAA) transistors, wide-bandgap materials like GaN and SiC, and ...

Researchers employ machine learning to more accurately model the boundary layer wind field of tropical cyclones. Conventional approaches to storm forecasting involve large numerical simulations run on ...

Zinc finger nucleases (ZFNs) have great potential for translational research and clinical use. Scientists succeeded in the efficient construction of functional ZFNs and the improvement of their genome ...

Advances in mechanistic modeling, machine learning, and biomedical data integration are making it possible to move beyond “one-size-fits-all” evidence and ...

Global climate models capture many of the processes that shape Earth's weather and climate. Based on physics, chemistry, fluid motion and observed data, hundreds of these models agree that more carbon ...

We independently evaluate all of our recommendations. If you click on links we provide, we may receive compensation. Michael is a former senior editor of investing and trading products for ...