A new study introduces a global probabilistic forecasting model that predicts when and where ionospheric disturbances—measured by the Rate of total electron content (TEC) Index (ROTI)—are likely to ...

Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions or values from labeled historical data, enabling precise signals such as ...

Sara Hooker, CEO of Adaption Labs, argues that the future of AI lies in adaptive learning rather than simply increasing model size.

Dr. James McCaffrey presents a complete end-to-end demonstration of decision tree regression from scratch using the C# language. The goal of decision tree regression is to predict a single numeric ...

Sara Hooker’s new startup Adaption Labs is challenging A.I.’s reliance on massive data and compute power with adaptive, real-time learning.

Microgrids play a growing role in modern power systems, supporting renewable integration, local resilience, and decentralized ...

My Creta Electric Excellence LR LogsThe culmination of a search that started from 2021 for the perfect vehicle for my dad, after comparing all ...

Abstract: To address the significant overhead of the beam training in millimeter wave (mmWave) wireless communications, we propose a balanced multimodal fusion network with bi-directional enhancement ...

Abstract: Distributed deep learning faces a major bottleneck in communication efficiency due to the frequent exchange of gradient information among computing nodes. Gradient compression offers a ...

This study presents a bio-inspired control framework for soft robots, enhancing tracking accuracy by over 44% under disturbances while maintaining stability.

The integration of deep reinforcement learning with PD control in humanoid robots enhances gait stability and patient comfort ...

The engineer behind AI lenses reaching 400 million Snapchat users explains how diffusion models, on-device inference, and ...