We introduce LaDCast, the first latent diffusion model for ensemble weather forecasting. It showcases the feasibility of using the latent approach for weather forecasting, which is an alternative ...

The deep learning revolution has a curious blind spot: the spreadsheet. While Large Language Models (LLMs) have mastered the nuances of human prose and image generators have conquered the digital ...

Cisco and Splunk have introduced the Cisco Time Series Model, a univariate zero shot time series foundation model designed for observability and security metrics. It is released as an open weight ...

aDepartment of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA bResearch Laboratory for Electronics, Massachusetts Institute of Technology ...

The Clock Is Ticking for New Mexico to Cut Rio Grande Water Use Trump Lashes Out at National Academies of Sciences Over Climate Guide For Judges The Thriving Coral Reef That ‘Defeated Time’ in West ...

Abstract: This study combined linear discriminant analysis (LDA) and multivariate logistic regression models to systematically analyze key indicators in flood prediction, aiming to identify factors ...

Abstract: Long-term time-series forecasting is critical in nu-merous domains, including economics, climate modeling, and energy management. Traditional deep learning models often struggle with ...

Sea surface temperature (SST) variability plays a key role in the global weather and climate system, with phenomena such as El Niño-Southern Oscillation (ENSO) regarded as a major source of ...

Climate forecasts, both experimental and operational, are often made by calibrating Global Climate Model (GCM) outputs with observed climate variables using statistical and machine learning models.

aSchool of Public Health, Shanghai Institute of Infectious Disease and Biosecurity, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, Fudan ...