computation-graph

nlpodyssey/spago

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

dmlc/nnvm

dlsys-course/assignment1-2018

Assignment 1: automatic differentiation

gy910210/neural-network-from-scratch

Implementing Multiple Layer Neural Network from Scratch

TilliFe/Neural-Network-Playground

A visual Deep Learning Framework for the Web - Built with WebGPU, Next.js and ReactFlow.

dlsys-course/assignment2-2017

(Spring 2017) Assignment 2: GPU Executor

vankesteren/tensorsem

Structural Equation Modeling using Torch

HyTruongSon/GraphFlow

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]

invenia/Dispatcher.jl

Build, distribute, and execute task graphs

jgolebiowski/graphAttack

Computational graph library for machine learning

MahanFathi/Model-Based-RL

Model-based Policy Gradients

hyroai/computation-graph

zombie-einstein/jaxpr-viz

Jaxpr Visualisation Tool

Othoz/paragraph

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

wzh99/GenCoG

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

neonwatty/computational_maths

A short collection of Jupyter notebooks explaining some basic computational math

brunolange/artifax

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.

praisethemoon/cgraph

C computation graph, AutoGrad with OpenCL support [WIP]

CallumJHays/bdsim_realtime

Real-time execution and remote monitoring and tuning of BDSim Block-Diagrams for modeling and control of Dynamical Systems

arindas/arundel

Java library for building computation graphs.

fwcd/mini-ml

Computation graphs, automatic differentiation and machine learning for Kotlin

ucker/easy_neural_network

a single c++ file for learing how data flow graphs work.

BlaiseMuhirwa/gladius

An easy-to-use dynamic computation graph library for running e2e ML training.

isopropylcyanide/Interaction-Graph

Creating and analyzing interaction graphs based on boolean functions

martini9393/auto-diff

Assignment 1: automatic differentiation

semeniuta/EPypes

Python library for developing data processing algorithms as computational graphs and their integration with publish-subscribe systems

weberBen/Automatic_differentiation

Implementation of automatic differentiation (AD) in forward and backward modes with mathematical explanations

a2nfinance/deflow

To become a comprehensive platform for users to execute data processing and AI model training tasks using Ocean nodes within the C2DV2 architecture.

martini9393/gpu-executor

Assignment 2: GPU Executor

yvn11/infinity

DAG-based computation graph for streaming data

disonvon/DPGA.py

This repository contains the code that produces the numeric section in On the Use of TensorFlow Computation Graphs in combination with Distributed Optimization to Solve Large-Scale Convex Problems

felidan/avic

Projeto de TCC baseado em processamento de imagens e visão computacional para identificar a evolução de ogras da engenharia civil

jhonec/Computer-Graphics-3D

These are my computer graphics projects.

krisht/CGML-Assignments

Code for projects and homework from ECE-491: Computational Graphs for Machine Learning (aka Deep Learning/Neural Nets)

byx2000/AutoDiff

Automatic derivative calculation of scalar functions.