Graph Neural Network Library for PyTorch

Base pretrained models and datasets in pytorch (MNIST, SVHN, CIFAR10, CIFAR100, STL10, AlexNet, VGG16, VGG19, ResNet, Inception, SqueezeNet)

A TensorFlow implementation of the Differentiable Neural Computer.

Random instruction generator for RISC-V processor verification

A PyTorch implementation of "Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks" (KDD 2019).

An abstraction library for interfacing EDA tools

Neural Turing Machine (NTM) & Differentiable Neural Computer (DNC) with pytorch & visdom

Reference implementations of neural networks with differentiable memory mechanisms (NTM, Stack RNN, etc.)

Explore the energy-efficient dataflow scheduling for neural networks.

Implementation of End-to-End Memory Network in PyTorch

Pytorch implementation of DeepMind's differentiable neural computer paper.

A library to create and manage configuration files, especially for machine learning projects.

[FPGA 2020] Open sourced implementation for the ACM/SIGDA FPGA '20 paper titled "GraphACT: Accelerating GCN Training on CPU-FPGA Heterogeneous Platforms"

Customization of waf to create a test framework and build tool for RTL

Converter of Synthesizable SystemVerilog to Verilog code