A multi-cloud MLOps framework improves AI service reliability through automated deployment, canary releases, and ...

The 360-degree camera market is accelerating at a disruptive pace, driven by immersive content demand, spatial computing, and rapid adoption across virtual reality ecosystems. Surging penetration in ...

Short-term forecasting of the Air Quality Index (AQI) can support public health risk management and real-time environmental decision-making. In this study, we propose a multivariate, one-step-ahead ...

New research reveals that ‘foundation models’ trained on vast, general time‑series data may be able to forecast river flows accurately, even in regions with little or no local hydrological records.

A unified foundation model for medical time series — pretrained on open access and ethics board-approved medical corpora — offers the potential to reduce annotation burdens, minimize model ...

This project provides a modern, well-structured implementation of hierarchical time series forecasting methods. It supports various forecasting algorithms (ARIMA, Prophet, LSTM) and reconciliation ...

Abstract: Irregular time series (ITS) data are widespread across healthcare, finance, and the Internet of Things (IoT), where accurate forecasting is crucial for applications such as disease ...

ABSTRACT: This paper investigates the application of machine learning techniques to optimize complex spray-drying operations in manufacturing environments. Using a mixed-methods approach that combines ...

Influenza remains a significant public health challenge worldwide, necessitating robust forecasting models to facilitate timely interventions and resource allocation. The aim of this study was to ...