Interpretable deep learning network significantly improves tropical cyclone intensity forecast accuracy

Predicting tropical cyclones (TCs) accurately is crucial for disaster mitigation and public safety. Although the forecasting accuracy of TC tracks has improved substantially in recent decades, ...

Jingtian Zhang Advances Personalized Advertising with a Deep Learning Framework for User Interest and Sentiment Analysis

A deep learning framework enhances personalized advertising by combining reinforcement learning, sentiment analysis, and user behavior ...
Frontiers

Spiking Neural Networks at Scale: Learning Algorithms, Architectures, and Real-World Applications

Spiking Neural Networks (SNNs) are a cutting-edge approach to artificial intelligence, designed to emulate the brain's architecture and functionality. Their ...
Unite.AI

DINOv3 and the Future of Computer Vision: Self-Supervised Learning at Scale

Labeling images is a costly and slow process in many computer vision projects. It often introduces bias and reduces the ability to scale large datasets. Therefore, researchers have been looking for ...
pharmaphorum

The AI drug discovery race: Who’s leading the charge?

In 2015, AI in drug discovery was still a theoretical pursuit – exciting, but unproven. A few early start-ups were applying deep learning to virtual screening and molecular modelling, but the industry ...