computation-graph

Gorgonia is a library that helps facilitate machine learning in Go.

Self-contained Machine Learning and Natural Language Processing library in Go

Assignment 1: automatic differentiation

Implementing Multiple Layer Neural Network from Scratch

(Spring 2017) Assignment 2: GPU Executor

Deep Learning framework in C++/CUDA that supports symbolic/automatic differentiation, dynamic computation graphs, tensor/matrix operations accelerated by GPU and implementations of various state-of-the-art graph neural networks and other Machine Learning models including Covariant Compositional Networks For Learning Graphs [Risi et al]

Structural Equation Modeling using Torch

Computational graph library for machine learning

Build, distribute, and execute task graphs

Efficient in-memory representation for ONNX, in Python

Jaxpr Visualisation Tool

Model-based Policy Gradients

GenCoG: A DSL-Based Approach to Generating Computation Graphs for TVM Testing (ISSTA‘23)

A computation graph micro-framework providing seamless lazy and concurrent evaluation

A short collection of Jupyter notebooks explaining some basic computational math

artifax is a Python package to evaluate nodes in a computation graph where the dependencies associated with each node are extracted directly from their function signatures.

C computation graph, AutoGrad with OpenCL support [WIP]

Incremental computation engine for Rust and Python: tracks dependencies between computations and only reruns what changed. Combines function DAGs with delta-based collections in a single runtime.