Are Machine Learning (ML) algorithms superior to traditional econometric models for GDP nowcasting in a time series setting? Based on our evaluation of all models from both classes ever used in ...

Modern consumer brands are confronting an uncomfortable truth: the products they once made for retail shelves often fail online. The search behavior, recommendation engines, AI assistants, and ...

Jim Simons's Medallion Fund averaged 66% annual returns for three decades, using math that would make ChatGPT weep Jim Simons was trying to solve a puzzle. Billions of dollars fell out when he cracked ...

As the world races to build artificial superintelligence, one maverick bioengineer is testing how much unprogrammed intelligence may already be lurking in our simplest algorithms to determine whether ...

Application security solutions provider Black Duck Software Inc. today announced the that it has added artificial intelligence model risk scanning to its Software Composition Analysis platform. The ...

📄 Please read the official article for more information about this open source software: Open source map matching with Markov decision processes: A new method and ...

The hidden Markov model (HMM), a statistical model widely applied in machine learning, has proven effective in addressing various problems in bioinformatics. Once primarily regarded as a mathematical ...

ABSTRACT: Traffic monitoring plays a vital role in smart city infrastructure, road safety, and urban planning. Traditional detection systems, including earlier deep learning models, often struggle ...

Non-invasive urine tests for bladder cancer (BC) could reduce dependence on flexible cystoscopy for diagnosis and surveillance. Most recent developments in urine testing are based on targeted ...

Sparse early-stage data limits accurate geological risk assessment, increasing the chance of undetected hazards ahead of the TBM. By integrating borehole-derived information through an observation ...