RNA has emerged as one of the most promising molecules in modern medicine, enabling advances from mRNA vaccines and gene ...

That admission is what some in the field call recursive self-improvement (RSI), the point at which large language models ...

In recent years, the frequency of weather-related natural disasters—cyclones, torrential rains, floods—has increased as a consequence of global warming. These disasters cause billions of dollars in ...

Build, test, and deploy ML-driven trading strategies — from data sourcing to live execution. This repository hosts the code for Machine Learning for Trading, 3rd Edition by Stefan Jansen — a ground-up ...

Abstract: Among various biometric methods, palm vein authentication has taken significant attention because of its uniqueness, stability and non-intrusiveness. In this paper, we propose a palm vein ...

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 ...

Abstract: Hyper parameter optimization (HPO) is a crucial step in modern machine learning systems. Bayesian optimization (BO) has shown great promise in HPO, where the parameter evaluation is ...

Model performance was evaluated using accuracy, balanced accuracy, Brier score, detection prevalence, F1-score, Jaccard index, κ coefficient, Matthews correlation coefficient, negative predictive ...

Accurate disaster prediction combined with reliable uncertainty quantification is crucial for timely and effective decision-making in emergency management. However, traditional deep learning methods ...

When Meta broke ground last year on its data center in Rosemount, Minn., about 15 miles south of Minneapolis and St. Paul, the social media giant faced a concrete paradox: the material’s carbon burden ...