Erlang node implemented in Python 3.5+ (Asyncio-based)

1. Use BERT, ALBERT and GPT2 as tensorflow2.0's layer. 2. Implement GCN, GAN, GIN and GraphSAGE based on message passing.

Source code for GNN-LSPE (Graph Neural Networks with Learnable Structural and Positional Representations), ICLR 2022

factor graph library

The official PyTorch implementation of "Pathfinder Discovery Networks for Neural Message Passing" (WebConf '21)

Gradient gating (ICLR 2023)

Concurrent, Asynchronous, Distributed, Communicating Tasks with Python

Linear Gaussian Bayesian Networks - Inference, Parameter Learning and Representation. 🖧

Belief propagation with sparse matrices (scipy.sparse) in Python for LDPC codes. Includes NumPy implementation of message passing (min-sum and sum-product) and a few other decoders.

Graph-based machine learning for chemical property prediction

Implementation for ReFactor GNNs

DGL implementation of GNN-CCA: Graph Neural Networks for Cross-Camera Data Association [arXiv:2201.06311]

Example of High-Speed Subscriber Patterns in ZeroMQ

Official Implementation of Multi-Masked Aggregators for Graph Neural Networks in Pytorch and PyTorch Geometric

Advanced Message Passing

COntagion Simulation And Source Identification: a Python package for graph diffusion source inference

An authenticated/secured message passing broker and clients

[ICML 2023] Official code for our paper: 'Conditional Tree Matching for Inference-Time Adaptation of Tree Prediction Models'

Refactored the Udaconnect app (from monolithic to microservices) and implemented Kafka, gRPC, and RESTful API to allow message passing between the microservices. I also created OpenAPI documentation for the API endpoints and provided a Postman library for the endpoints created.