Erlang node implemented in Python 3.5+ (Asyncio-based)
- Updated
Apr 9, 2025 - Python
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
Tsetlin Machine for Logical Learning and Reasoning With Graphs
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
DGL implementation of GNN-CCA: Graph Neural Networks for Cross-Camera Data Association [arXiv:2201.06311]
Implementation for ReFactor GNNs
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
CartNet repository to predict properties from crystal structures
COntagion Simulation And Source Identification: a Python package for graph diffusion source inference
[ICML 2023] Official code for our paper: 'Conditional Tree Matching for Inference-Time Adaptation of Tree Prediction Models'
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