Frontiers

Signal Processing for Representation Learning: Theoretical Foundations and Emerging Applications

Representation learning lies at the core of modern artificial intelligence, enabling neural networks to uncover meaningful, ...

Keeping long-term climate simulations stable and accurate with a new AI approach

Hybrid climate modeling has emerged as an effective way to reduce the computational costs associated with cloud-resolving ...
IEEE

Deep Reinforcement Learning-Based Resource Allocation for Hybrid Bit and Generative Semantic Communications in Space-Air-Ground Integrated Networks

Abstract: In this paper, we introduce a novel framework consisting of hybrid bit-level and generative semantic communications for efficient downlink image transmission within space-air-ground ...
Psychology Today

Why the New Artificial Intelligence Is So Powerful

AI became powerful because of interacting mechanisms: neural networks, backpropagation and reinforcement learning, attention, ...
IEEE

Autonomous Navigation of UAVs in Unknown 3D Environments Using Deep Reinforcement Learning for Path Planning

Abstract: Much research has been conducted on unmanned aerial vehicles (UAVs) across various fields. Due to the obstacle-ridden environments, there is a strong need for a high-performance autonomous ...