Abstract: Power and energy balancing technology is at the core of smart grids. Expert subjective judgments play a critical role in the balancing control process. However, due to the subjectivity, ...

An AI model that learns without human input—by posing interesting queries for itself—might point the way to superintelligence. Save this story Save this story Even the smartest artificial intelligence ...

Abstract: Using a privacy-preserving federated hybrid architecture that combines Long Short-Term Memory (LSTM) and Multilayer Perceptron networks (MLP), the research suggests a novel method. Our ...

PyTorch Lightning implementation of an LSTM-based encoder-decoder for battery aging prediction. The model is optimized for training/prediction speed and prediction accuracy and can be applied for ...

In a new comparative analysis of artificial intelligence applications in retail, researchers have revealed that advanced deep learning models can dramatically enhance the accuracy of demand ...

This project implements state-of-the-art deep learning models for financial time series forecasting with a focus on uncertainty quantification. The system provides not just point predictions, but ...

While much of the activity in the AI markets are focused on the tech giants chasing ever-increasing model sizes and compute budgets, financial company FICO is going the other way with smaller, smarter ...

For the field of drug development, hitting the right target with atomic precision to achieve therapeutic effect remains the core challenge. While traditional R&D pipelines are dependent on ...

With the widespread application of lithium-ion batteries in electric vehicles and energy storage systems, health monitoring and remaining useful life prediction have become critical components of ...