Here are strategic revision techniques, important topics, diagram practice, and exam-day strategies to help CBSE Class 12 ...

From talking cars that sounded like depressed robots to automatic seatbelts that attacked passengers like automotive boa ...

Looking for good code examples for LeetCode problems? You’re in luck! Lots of people share their solutions online, especially ...

As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models designed to process graph-structured data. Currently, GNNs are effective ...

Enterprise AI can’t scale without a semantic core. The future of AI infrastructure will be built on semantics, not syntax.

Google’s artificial intelligence research laboratory where AlphaFold was developed—has officially released a new machine ...

Abstract: There is a vast literature on representation learning based on principles such as coding efficiency, statistical independence, causality, controllability, or symmetry. In this paper we ...

Abstract: Representing and exploiting multivariate signals requires capturing relations between variables, which we can represent by graphs. Graph dictionaries allow to describe complex relational ...

The official implementation of WACV 2026 paper UNO: Unifying One-stage Video Scene Graph Generation via Object-Centric Visual Representation Learning Video Scene Graph Generation (VidSGG) aims to ...

1 Department of Analytics, Harrisburg University of Science and Technology, Harrisburg, PA, United States 2 Department of Emergency Medicine, UMass Chan Medical School, Worcester, MA, United States ...

This course provides a complete learning path from neural network basics to cutting-edge architectures like Transformers, GANs, and Graph Neural Networks. Each chapter includes theoretical ...