IEEE

An Effective Summary Preprocessing Method for Time Series Forecasting With Multiple Temporal Granularities

Abstract: Time-series forecasting plays a pivotal role in decision-making. Recently, as deep learning models have shown exceptional performance in time-series forecasting, research in the field of ...
IEEE

Time Series Forecasting via Reinforcement-Learning-Based Model Combination

Abstract: Time series data permeates our daily existence and has been recognized as of significant importance for many sectors, such as energy, transportation, telecommunication, and health care.
Power Technology

Redefining load forecasting and management: how AI is making smart grids smarter

Legacy load forecasting models are struggling with ever-more-common, unpredictable events; power-hungry AI offers a solution.
International Monetary Fund

Satellite Data for Nowcasting: Estimating Cambodia’s GDP in Real Time Using Satellite Data in a Machine Learning Framework

Cambodia is not alone in facing capacity limitations in the production and timely release of key official statistics needed for data-driven policy decisions. This paper demonstrates that combining ...
GitHub

Dynamic Cheatsheet: Test-Time Learning with Adaptive Memory

A lightweight framework that gives language models (LMs) a persistent, evolving memory during inference time. Dynamic Cheatsheet (DC) endows black-box language models with the ability to store and ...