Nearing et al., (2022) Technical Note: Data assimilation and autoregression for using near-real-time streamflow observations in long short-term memory networks. Hydrology and Earth Systems Science ...

Have you ever imagined predicting your company’s revenue for the coming months based on past data? This is the power of time series forecasting, which analyzes data organized chronologically, such as ...

It has long been the goal to use quantum-mechanical (QM) simulations for high-throughput materials screening and design 1. This goal, however, remains elusive given the prohibitive computational costs ...

Understanding the interplay between multiple variables is critical to accurate forecasting and strategic decision-making in modern enterprise environments. Vector Autoregression (VAR) is a powerful ...

This code has been tested on Ubuntu 20.04 with Python 3.8.18 and PyTorch 2.2.1 using CUDA 12.1. To install the required packages, run the following command: conda env create -f conda_env_cuda12.1.yaml ...

Abstract: Accurate forecasting of stock prices is becoming increasingly important in stock markets where returns and risks are highly volatile. The paper compares the accuracy of conventional time ...

Reservoir computing is a best-in-class machine learning algorithm for processing information generated by dynamical systems using observed time-series data. Importantly, it requires very small ...