Gorgonia is a library that helps facilitate machine learning in Go.
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Updated
May 21, 2024 - Go
Gorgonia is a library that helps facilitate machine learning in Go.
Implementing Multiple Layer Neural Network from Scratch
Self-contained Machine Learning and Natural Language Processing library in Go
(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]
Computational graph library for machine learning
A visual Deep Learning Framework for the Web - Built with WebGPU, Next.js and ReactFlow.
Build, distribute, and execute task graphs
A short collection of Jupyter notebooks explaining some basic computational math
Model-based Policy Gradients
Python library for developing data processing algorithms as computational graphs and their integration with publish-subscribe systems
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.
GenCoG: A DSL-Based Approach to Generating Computation Graphs for TVM Testing (ISSTA‘23)
Creating and analyzing interaction graphs based on boolean functions
C computation graph, AutoGrad with OpenCL support [WIP]
Implementation of automatic differentiation (AD) in forward and backward modes with mathematical explanations
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