Deep universal probabilistic programming with Python and PyTorch

InferPy: Deep Probabilistic Modeling with Tensorflow Made Easy

a python framework to build, learn and reason about probabilistic circuits and tensor networks

A collection of Methods and Models for various architectures of Artificial Neural Networks

A scalable and accurate probabilistic network configuration analyzer verifying network properties in the face of random failures.

Sum-product networks in Julia.

Distributional Gradient Boosting Machines

An extension of Py-Boost to probabilistic modelling

A normalizing flow using Bernstein polynomials for conditional density estimation.

A toolbox for inference of mixture models

Blackjack Notebook (bjnb): Probabilistic analysis and simulation

Repository to reproduce "Cascade-based Echo Chamber Detection" accepted at CIKM2022

Extended functionality for univariate probability distributions in PyTorch

Train and evaluate probabilistic word embeddings with Python.

Scalable probabilistic impact modeling

Tensor-Network Machine Learning with Matrix Product States, trained via a surrogate (projective) loss instead of standard negative log-likelihood

Flask-based probabilistic discrete optimization web app deployed on Vercel with Neon (PostgreSQL).

This repository introduces an adaptive formula inspired by the CHSH logic, designed to evaluate, test, and improve model performance across multiple conditions. By adapting CHSH principles into a flexible structure, it provides a systematic way to analyze results, ensure reliability, and explore deeper insights in experimentation.

Materials for my course SOCI 3040, Quantitative Research Methods

This project explores a novel approach to forecasting by leveraging probabilistic reasoning to model future events before they occur.

Probabilistic Programming with Python and Chainer

From-scratch C++23 AI algorithms with Eigen (ML, DL, RL, evolutionary, probabilistic, graph, and causal) built with CMake/vcpkg.

No description provided.

Probabilistic ML framework for RUL prediction combining neural networks and Bayesian particle filtering for uncertainty-aware prognostics.

No description provided.

Mathematical explorations and first-principles implementations of core machine learning methods.

🚀 Orchestrate your machine learning workflows with RoadML Pipeline, an enterprise solution for managing end-to-end ML lifecycle efficiently.

Cloud-native multi-horizon market forecasting platform with probabilistic predictions, confidence scoring, and production-grade ML infrastructure.

Probabilistic simulation of AFCON Morocco 2025: group stage, knockouts, and winner prediction.

A comprehensive Sentiment Analysis project on Twitter data using Natural Language Processing (NLP). It includes custom text preprocessing (Stemming, Tokenization) and implements a probabilistic classification model to distinguish between positive and negative sentiments with high accuracy.