Python-first access to R’s brms with proper parameter names, ArviZ support, and cmdstanr performance. The easiest way to run brms models from Python.

Parallelized MLDA Sampler based on Prefetching

This repository contains the implementation of Enhanced Random Binary Multilevel Attention Network (ERBMA-Net), a novel framework for facial depression recognition. ERBMA-Net addresses key limitations in existing methods by introducing random binary convolutional filters for enhanced adaptability and multilevel attention mechanisms.

This project evaluates the relationship between YouTube video comment engagement and sentiment and finds that positive sentiment increases engagement.

This project applies Data Analysis using python libraries to a longitudinal dataset to explore the relationship between a child's age, expressive language skills, and their socialization development. A multilevel modeling approach is used to account for the correlated, repeated measurements taken from each child over several years.

benchmark analysis of sorting algorithms with multi-level attribute comparisons for resolving duplicate entries in real-world datasets, including cross-platform performance metrics