A curated list of neural network pruning resources.

Awesome machine learning model compression research papers, quantization, tools, and learning material.

Repository to track the progress in model compression and acceleration

Tensor decomposition implemented in TensorFlow

TedNet: A Pytorch Toolkit for Tensor Decomposition Networks

An implementation of various tensor-based decomposition for NN & RNN parameters

Reducing the computational overhead of Deep CNNs through parameter pruning and tensor decomposition.

HOTTBOX: Higher Order Tensors ToolBOX.

🎓 International Joint Conference on Neural Networks (IJCNN) 14-19 July 2019 || Materials for the tutorial "Tensor Decompositions for Big Data Analytics: Trends and Applications"

Best Practices, code samples, and documentation for Computer Vision.

一隻聊天機器人他會展示全國販售口罩的藥局。

[NeurIPS 2019, Spotlight] Point-Voxel CNN for Efficient 3D Deep Learning

Models and examples built with TensorFlow

An implementation of 'Deep Bilateral Learning for Real-Time Image Enhancement', SIGGRAPH 2017

A framework for multiframe super-resolution (enhancing the quality of an image from multiple similar low-resolution images) with support for hyperspectral imaging data.

A general framework for optimizing DNN dataflow on systolic array

A invariant-based stereo matching algorithm

Tensorflow 2.x based implementation of EDSR, WDSR and SRGAN for single image super-resolution

Must-read papers on graph neural networks (GNN)

A repository for code accompanying my Medium posts.

PyTorch implementations of deep reinforcement learning algorithms and environments

Multi-frame super-resolution via sub-pixel.

Demo code of the paper "Fast and Accurate Online Video Object Segmentation via Tracking Parts", in CVPR 2018

Practical assignments of the Deep|Bayes summer school 2019

SUper REsolution MEthods

⚡️ A framework for building conversational user interfaces.