An AI-driven digital-predistortion (DPD) framework can help overcome the challenges of signal distortion and energy ...

In the previous chapter, we learned various strategies to guide AI models 'down the mountain' (optimization algorithms), such ...

A highly regarded research direction is “Physical Neural Networks” (PNNs), which utilize physical systems like light, ...

Dr. James McCaffrey presents a complete end-to-end demonstration of the kernel ridge regression technique to predict a single ...

ABSTRACT: Background: Treatment-resistant depression (TRD) poses significant clinical challenges, with many patients inadequately responding to augmentation strategies like aripiprazole. Pramipexole, ...

You can create a release to package software, along with release notes and links to binary files, for other people to use. Learn more about releases in our docs.

ABSTRACT: Accurate precipitation forecasting is crucial for mitigating the impacts of extreme weather events and enhancing disaster preparedness. This study evaluates the performance of Long ...

Rzeszow University of Technology researchers based in Rzeszow, Poland predicted concentration profiles in gradient liquid chromatography (GLC) using physics-informed neural networks (PINNs). Their ...

You can create a release to package software, along with release notes and links to binary files, for other people to use. Learn more about releases in our docs.