An AI assistant for high-entropy alloy (HEA) electrocatalysis named ChatHEA provided a helping hand not just to extract data ...

Prediction markets have quietly become one of the most interesting corners of the tech world. From forecasting elections to predicting sports outcomes and even guessing the next big product launch, ...

A research team at The Hong Kong Polytechnic University (PolyU) has developed Hong Kong's first "AI Agent for Precision ...

Every year from May through October, the United States enters what climate scientists and emergency managers now call “Danger Season,” a six-month gauntlet of compounding climate hazards when ...

Wildfire survivors call fire-prediction markets “morally reprehensible” and worry they could increase the risk of arson.

This repository includes the training and evaluation code for the above paper. python train_script.py --name data_physics --data True --physics True --pretrained_checkpoint DATA_CHECKPOINT ...

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

Supervised machine learning improves predictions of compressive strength in industrial waste-modified concrete, supporting ...

Hy 2 DL is a python library to create hydrological models for rainfall-runoff prediction using deep learning methods. The repository includes implementations with Large-Sample Hydrology datasets such ...

Abstract: Adversarial examples represent a serious threat for deep neural networks in several application domains and a huge amount of work has been produced to investigate them and mitigate their ...

Abstract: Forecasted global horizontal irradiation (GHI) can help for designing, sizing and performances analysis of photovoltaic (PV) systems including water PV pumping systems used for irrigation ...