Researchers at Seoul National University and Kyung Hee University report a framework to control collective motions, such as ring, clumps, mill, flock, by training a physics-informed AI to learn the ...

Learn how free IIT courses on SWAYAM are breaking barriers, offering quality education, and helping students and ...

Overview PyTorch and JAX dominate research while TensorFlow and OneFlow excel in large-scale AI trainingHugging Face ...

Abstract: The paper focuses on the development of a software program for creating and training ANN (artificial neural network) models. This program allows users to create their own ANN models without ...

An AI-driven digital-predistortion (DPD) framework can help overcome the challenges of signal distortion and energy inefficiency in power amplifiers for next-generation wireless communication.

A recent Nature study shows that separated artificial neural networks can accurately model SiC MOSFETs using minimal training data. Silicon carbide MOSFETs are increasingly replacing traditional ...

This video is an overall package to understand Dropout in Neural Network and then implement it in Python from scratch. Dropout in Neural Network is a regularization technique in Deep Learning to ...

Megan Cerullo is a New York-based reporter for CBS MoneyWatch covering small business, workplace, health care, consumer spending and personal finance topics. She regularly appears on CBS News 24/7 to ...

This article is part of an ongoing column on AI and planning by urban planner and AI expert, Tom Sanchez. Read more installments here. Urban planners aren’t expected to become AI engineers. But with ...

Myoelectric control systems translate electromyographic signals (EMG) from muscles into movement intentions, allowing control over various interfaces, such as prosthetics, wearable devices, and ...