Both Kalshi and Polymarket, the two big prediction market platforms, were offering yes-or-no-style “mention markets” asking ...

AI fixes earnings forecasting when it expands coverage, standardizes signal extraction, and quantifies uncertainty. AI breaks forecasting when it creates false precision, synchronized expectations, ...

Tabular foundation models are the next major unlock for AI adoption, especially in industries sitting on massive databases of ...

These open-source MMM tools solve different measurement problems, from budget optimization to forecasting and preprocessing.

SmurphCast – percentage‑first time‑series forecasting (churn, CTR, conversion, retention) with additive + GBM + ES‑RNN stacking and automatic model selection. 100 % Python, CPU‑friendly, explainable.

The Aurora Borealis put on an impressive showing Tuesday night, and there’s potential for it to dance in the sky again Wednesday. kP indices peaked near 9 p.m. on Nov. 11, allowing for the Northern ...

A comprehensive time series analysis project that uses various forecasting techniques to predict book sales and demand patterns. This project analyzes historical sales data from Nielsen BookScan to ...

In this tutorial, we build an advanced agentic AI system that autonomously handles time series forecasting using the Darts library combined with a lightweight HuggingFace model for reasoning. We ...

Abstract: The rise of decentralized energy sources and renewables demands advanced grid planning, with short-term load forecasting (STLF) playing a crucial role. Energy demand in smart grids is highly ...

1 Chongqing Key Laboratory of Childhood Nutrition and Health, Department of Nephrology, Children's Hospital of Chongqing Medical University, National Clinical Research Center for Child Health and ...

Temperature impacts every part of the world. Meteorological analysis and weather forecasting play a crucial role in sustainable development by helping reduce the damage caused by extreme weather ...