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

Across the retail sector, the competitive frontier is shifting from who captures data to who can transform that data into ...

This important study introduces a new biology-informed strategy for deep learning models aiming to predict mutational effects in antibody sequences. It provides solid evidence that separating ...

Introduction Application of artificial intelligence (AI) tools in the healthcare setting gains importance especially in the domain of disease diagnosis. Numerous studies have tried to explore AI in ...

Abstract: Road administrators require fine-scaled information regarding road surface conditions to ensure efficient operation during winter periods. However, conventional models offer low-resolution ...

Anyone preparing for quant interviews must develop depth across several skill areas and know how to apply theory in a ...

This important study combines optogenetic manipulations and wide-field imaging to show that the retrosplenial cortex controls behavioral responses to whisker deflection in a context-dependent manner.

Abstract: Credit card fraud detection presents a significant challenge due to the extreme class imbalance in transaction datasets. Traditional machine learning models struggle to achieve high recall ...

This repository contains the code and documentation for a project that focuses on predicting stock market prices using LSTM models and optimizing a portfolio based on these predictions. Objective: ...

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 ...