In this tutorial, we demonstrate how we simulate a privacy-preserving fraud detection system using Federated Learning without relying on heavyweight frameworks or complex infrastructure. We build a ...

Abstract: Representing hyperspectral images (HSIs) is a complex and challenging task, primarily due to spectral uncertainty. The learnable prototypical contrastive learning is specialized in ...

AI vs robotics highlights the essential difference between intelligence and physical automation. Artificial intelligence interprets data, predicts patterns, and performs cognitive tasks such as image ...

We provide our PyTorch implementation of unpaired image-to-image translation based on patchwise contrastive learning and adversarial learning. No hand-crafted loss and inverse network is used.

Abstract: Graph contrastive learning (GCL) is emerging as a pivotal technique in graph representation learning. However, recent research indicates that GCL is vulnerable to adversarial attacks, while ...

Developers are navigating confusing gaps between expectation and reality. So are the rest of us. Depending who you ask, AI-powered coding is either giving software developers an unprecedented ...