The seven companies listed here cover the realistic range of what a buyer will encounter in 2026: embedded ML teams that own ...

How can sales figures be forecast more reliably, production capacities planned fully digitally, and employee know-how ...

Coastal and nearshore zones face growing pressure from storms, flooding, erosion, and sea-level rise, which threaten civil infrastructure such as ports, ...

The new SF Fed Policy Calibration Tool is designed to help construct a monetary policy path that aligns with one’s views of ...

The last time the tropical Pacific ran this hot, millions of people starved. The El Niño of 1877 triggered crop failures from India to Brazil and is considered one of the deadliest climate events 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 ...

This code is the official PyTorch implementation of our KDD'25 paper: DUET: Dual Clustering Enhanced Multivariate Time Series Forecasting. If you find this project helpful, please don't forget to give ...

Abstract: Multivariate time series forecasting plays a critical role in fields such as finance, health, weather, and energy. However, multivariate time series data encountered in real-world settings ...

Forecasting dynamic weather patterns like the January winter storm is not a simple task. Meteorologists pore over hundreds of computer-generated models predicting atmospheric conditions such as ...

After a merciful lack of hurricanes in the U.S. and an unusually quiet Gulf of Mexico, the 2025 Atlantic hurricane season wasn’t too memorable in Louisiana. But the season will be remembered for ...

The National Oceanic and Atmospheric Administration has introduced a new suite of weather forecasting models that are driven by Artificial Intelligence and are expected to deliver faster and more ...