Researchers have employed Bayesian neural network approaches to evaluate the distributions of independent and cumulative ...

Incrementality testing in Google Ads is suddenly within reach for far more advertisers than before. Google has lowered the barriers to running these tests, making lift measurement possible even ...

CNN in deep learning is a special type of neural network that can understand images and visual information. It works just like human vision: first it detects edges, lines and then recognizes faces and ...

This project implements a comprehensive Fuzzy Bayesian Network (FBN) system that combines fuzzy logic with probabilistic reasoning for advanced cybersecurity risk assessment. The system handles ...

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 ...

Cross-sectional network analysis was employed to explore the complex relationships between depression, anxiety, insomnia, somatic symptoms, childhood trauma, self-esteem, social support, and emotional ...

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

With the rapid development of industrialization and urbanization, the issue of water quality deterioration has become increasingly severe. Accurately assessing water quality is crucial for ...