Frontiers

A guide to bayesian networks software for structure and parameter learning, with a focus on causal discovery tools

A representation of the cause-effect mechanism is needed to enable artificial intelligence to represent how the world works. Bayesian Networks (BNs) have proven to be an effective and versatile tool ...
GitHub

Vector Autoregression (VAR) Analysis of U.S. Monetary Policy

In the current macroeconomic environment characterized by complex interactions between monetary policy, labor markets, and price dynamics, traditional single-equation models fail to capture the ...
IEEE

Grouped Vector Autoregression Reservoir Computing Based on Randomly Distributed Embedding for Multistep-Ahead Prediction

Abstract: As an efficient recurrent neural network (RNN), reservoir computing (RC) has achieved various applications in time-series forecasting. Nevertheless, a poorly explained phenomenon remains as ...
IEEE

Sparse Non-Linear Vector Autoregressive Networks for Multivariate Time Series Anomaly Detection

Abstract: Anomaly detection in multivariate time series (MTS) is crucial in domains such as industrial monitoring, cybersecurity, healthcare, and autonomous driving. Deep learning approaches have ...
Scientific Research Publishing

Utilizing the Vector Autoregression Model (VAR) for Short-Term Solar Irradiance Forecasting ()

Forecasting solar irradiance is a critical task in the renewable energy sector, as it provides essential information regarding the potential energy production from solar panels. This study aims to ...