Python Compression-artifact-reduction Resources

Code release for "Bayesian Compression for Deep Learning" In "Bayesian Compression for Deep Learning" we adopt a Bayesian view for the compression of

Towards Flexible Blind JPEG Artifacts Removal (FBCNN, ICCV 2021)

This repository contains the code for the paper in Findings of EMNLP 2021: "EfficientBERT: Progressively Searching Multilayer Perceptron via Warm-up Knowledge Distillation".

Must-read papers on improving efficiency for pre-trained language models.

Channel Pruning for Accelerating Very Deep Neural Networks (ICCV'17)

Conda-Vendor Conda Vendor is a tool to create local conda channels and manifests for vendored deployments Installation To install with pip, run: pip i

This repository is used to suspend the results of our paper "A Deep Learning Loss Function based on Auditory Power Compression for Speech Enhancement"

InvCompress Official Pytorch Implementation for "Enhanced Invertible Encoding for Learned Image Compression", ACMMM 2021 (Oral) Figure: Our framework

SwinIR: Image Restoration Using Swin Transformer This repository is the official PyTorch implementation of SwinIR: Image Restoration Using Shifted Win

Online Multi-Granularity Distillation for GAN Compression (ICCV2021) This repository contains the pytorch codes and trained models described in the IC

Tzar: Tar, Zip, Anything Really Easy compression and extraction for any compression or archival format. Usage/Examples tzar compress large-dir compres

Gorilla Time Series Compression This is an implementation (with some adaptations) of the compression algorithm described in section 4.1 (Time series c

SeerNet This is the pytorch implementation for the paper: Learning Accurate Performance Predictors for Ultrafast Automated Model Compression, which is

LTP: Learned Token Pruning for Transformers Check our paper for more details. Installation We follow the same installation procedure as the original H

DataFree A benchmark of data-free knowledge distillation from paper "Contrastive Model Inversion for Data-Free Knowledge Distillation" Authors: Gongfa

NeuralCompression is a Python repository dedicated to research of neural networks that compress data. The repository includes tools such as JAX-based entropy coders, image compression models, video compression models, and metrics for image and video evaluation.

Scalable Incomplete Network Embedding ⠀⠀ A PyTorch implementation of Scalable Incomplete Network Embedding (ICDM 2018). Abstract Attributed network em

A Closer Look at Structured Pruning for Neural Network Compression Code used to reproduce experiments in https://arxiv.org/abs/1810.04622. To prune, w

Chasing Sparsity in Vision Transformers: An End-to-End Exploration Codes for [Preprint] Chasing Sparsity in Vision Transformers: An End-to-End Explora

Spectral Tensor Train Parameterization of Deep Learning Layers This repository is the official implementation of our AISTATS 2021 paper titled "Spectr

HoroPCA This code is the official PyTorch implementation of the ICML 2021 paper: HoroPCA: Hyperbolic Dimensionality Reduction via Horospherical Projec

Group Fisher Pruning for Practical Network Compression (ICML2021) By Liyang Liu*, Shilong Zhang*, Zhanghui Kuang, Jing-Hao Xue, Aojun Zhou, Xinjiang W

Deep Networks from the Principle of Rate Reduction This repository is the official NumPy implementation of the paper Deep Networks from the Principle

HUMAP Hierarchical Manifold Approximation and Projection (HUMAP) is a technique based on UMAP for hierarchical non-linear dimensionality reduction. HU

CAT arXiv Pytorch implementation of our method for compressing image-to-image models. Teachers Do More Than Teach: Compressing Image-to-Image Models Q

You Only Compress Once: Towards Effective and Elastic BERT Compression via Exploit-Explore Stochastic Nature Gradient (paper) @misc{zhang2021compress,

Learning Invariant Representation for Unsupervised Image Restoration (CVPR 2020) Introduction This is an implementation for the paper "Learning Invari

TR-BERT Source code and dataset for "TR-BERT: Dynamic Token Reduction for Accelerating BERT Inference". The code is based on huggaface's transformers.

The lottery ticket hypothesis (LTH) reveals the existence of winning tickets (sparse but critical subnetworks) for dense networks, that can be trained in isolation from random initialization to match the latter’s accuracies.

Overview Pytorch code of our recent work A Unified End-to-End Framework for Efficient Deep Image Compression. We first release the code for Variationa

Nested-Co-teaching (L2ID@CVPR2021) Pytorch implementation of paper "Boosting Co-teaching with Compression Regularization for Label Noise" [PDF] If our

Deep Networks from the Principle of Rate Reduction This repository is the official PyTorch implementation of the paper Deep Networks from the Principl

DEPOCO This repository implements the algorithms described in our paper Deep Compression for Dense Point Cloud Maps. How to get started (using Docker)

Genshin Artifact Scraper Automatically scrape all of your artifacts in Genshin Impact. Features: Simple recalibration (2 steps). GUI to select OCR reg

PyKale is a PyTorch library for multimodal learning and transfer learning as well as deep learning and dimensionality reduction on graphs, images, texts, and videos. By adopting a unified pipeline-based API design, PyKale enforces standardization and minimalism, via reusing existing resources, reducing repetitions and redundancy, and recycling learning models across areas.

I-BERT: Integer-only BERT Quantization HuggingFace Implementation I-BERT is also available in the master branch of HuggingFace! Visit the following li

COIN 🌟 This repo contains a Pytorch implementation of COIN: COmpression with Implicit Neural representations, including code to reproduce all experim

Dynamic Slimmable Network (DS-Net) This repository contains PyTorch code of our paper: Dynamic Slimmable Network (CVPR 2021 Oral). Architecture of DS-

CDFI (Compression-Driven-Frame-Interpolation) [Paper] (Coming soon...) | [arXiv] Tianyu Ding*, Luming Liang*, Zhihui Zhu, Ilya Zharkov IEEE Conference

[ICLR 2021] "UMEC: Unified Model and Embedding Compression for Efficient Recommendation Systems" by Jiayi Shen, Haotao Wang*, Shupeng Gui*, Jianchao Tan, Zhangyang Wang, and Ji Liu

A curated list of neural network pruning and related resources. Inspired by awesome-deep-vision, awesome-adversarial-machine-learning, awesome-deep-learning-papers and Awesome-NAS.

BiPointNet: Binary Neural Network for Point Clouds Created by Haotong Qin, Zhongang Cai, Mingyuan Zhang, Yifu Ding, Haiyu Zhao, Shuai Yi, Xianglong Li

BoostARoota A Fast XGBoost Feature Selection Algorithm (plus other sklearn tree-based classifiers) Why Create Another Algorithm? Automated processes l

Master status: Development status: Package information: MDR A scikit-learn-compatible Python implementation of Multifactor Dimensionality Reduction (M

BitPack is a practical tool that can efficiently save quantized neural network models with mixed bitwidth.

Automatic text summarizer Simple library and command line utility for extracting summary from HTML pages or plain texts. The package also contains sim

ivis Implementation of the ivis algorithm as described in the paper Structure-preserving visualisation of high dimensional single-cell datasets. Ivis

openTSNE openTSNE is a modular Python implementation of t-Distributed Stochasitc Neighbor Embedding (t-SNE) [1], a popular dimensionality-reduction al

UMAP Uniform Manifold Approximation and Projection (UMAP) is a dimension reduction technique that can be used for visualisation similarly to t-SNE, bu

Automatic text summarizer Simple library and command line utility for extracting summary from HTML pages or plain texts. The package also contains sim

ivis Implementation of the ivis algorithm as described in the paper Structure-preserving visualisation of high dimensional single-cell datasets. Ivis

openTSNE openTSNE is a modular Python implementation of t-Distributed Stochasitc Neighbor Embedding (t-SNE) [1], a popular dimensionality-reduction al

UMAP Uniform Manifold Approximation and Projection (UMAP) is a dimension reduction technique that can be used for visualisation similarly to t-SNE, bu

Getting to the meat of g-code. Easy, fast, effective, and automatic g-code compression! MeatPack nearly doubles the effective data rate of a standard

FullSubNet This Git repository for the official PyTorch implementation of "A Full-Band and Sub-Band Fusion Model for Real-Time Single-Channel Speech E

Automatic text summarizer Simple library and command line utility for extracting summary from HTML pages or plain texts. The package also contains sim