In a security advisory, the researchers said that around April 2025, they discovered bugs in three open source Python ...

capellambse allows you reading and writing Capella models from Python without Java or the Capella tool on any (reasonable) platform. We wanted to "talk" to Capella models from Python, but without any ...

Discover how credibility theory helps actuaries use historical data to estimate risks and set insurance premiums; learn how ...

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

Abstract: This article presents a novel deep learning model, the Attentive Bayesian Multi-Stage Forecasting Network (ABMF-Net), designed for robust forecasting of electricity price (USD/MWh) and ...

ABSTRACT: This study examined the relationship between the Monetary Policy Rate (MPR) and inflation across five continents from 2014 to 2023 using both Frequentist and Bayesian Linear Mixed Models ...

In this work we present two main contributions: the first one is a Python implementation of the discrete approximation of the Laplace-Beltrami operator (LBO) (Belkin et al., 2008) allowing us to solve ...

Introduction: Cognitive impairment is a core feature of major depressive disorder (MDD) that often persists during remission, significantly affecting psychosocial functioning. While exercise is known ...

Incrementality testing in Google Ads is suddenly within reach for far more advertisers than before. Google has lowered the barriers to running these tests, making lift measurement possible even ...

Abstract: Sparse Bayesian learning (SBL) is an algorithm for high-dimensional data processing based on Bayesian statistical theory. Its goal is to improve the generalization ability and efficiency of ...