entropy-coding
There are 4 repositories under entropy-coding topic.
Justin-Tan / high-fidelity-generative-compression
Pytorch implementation of High-Fidelity Generative Image Compression + Routines for neural image compression
Language:Python 426iAvoe / x264-x265-QAAC-ffprobe-Ultimatetutorial
主打解析编码器内部逻辑和参数说明，从基础到全网没人讲的算法，没人画的图解，没人做的排版整理全都在此集齐；因此叫Ultimate Tutorial
Language:CSS 138bamler-lab / constriction
Entropy coders for research and production in Python and Rust.
Language:Rust 84- ArithmeticEncodingPython
ahmedfgad / ArithmeticEncodingPython
Data Compression using Arithmetic Encoding in Python
Language:Python 77 aika-algorithm / aika
AIKA is a new type of artificial neural network designed to more closely mimic the behavior of a biological brain and to bridge the gap to classical AI. A key design decision in the Aika network is to conceptually separate the activations from their neurons, meaning that there are two separate graphs. One graph consisting of neurons and synapses representing the knowledge the network has already acquired and another graph consisting of activations and links describing the information the network was able to infer about a concrete input data set. There is a one-to-many relation between the neurons and the activations. For example, there might be a neuron representing a word or a specific meaning of a word, but there might be several activations of this neuron, each representing an occurrence of this word within the input data set. A consequence of this decision is that we have to give up on the idea of a fixed layered topology for the network, since the sequence in which the activations are fired depends on the input data set. Within the activation network, each activation is grounded within the input data set, even if there are several activations in between. This means links between activations serve two purposes. On the one hand, they are used to sum up the synapse weights and, on the other hand they propagate the identity to higher level activations.
Language:Java 75- Turbo-Range-Coder
powturbo / Turbo-Range-Coder
TurboRC - Fastest Range Coder + Arithmetic Coding / Fastest Asymmetric Numeral Systems
Language:C 73 - Language:C 66
weissenberger / gpuhd
Massively Parallel Huffman Decoding on GPUs
Language:C++ 44tongdaxu / YAECL-Yet-Another-Entropy-Coding-Library
YAECL: Yet Another Entropy Coding Library for Neural Compression Research, with Arithmetic Coding and Asymmetric Numeral Systems support
Language:C++ 35Nikolai10 / MRIC
TensorFlow implementation of MRIC (Multi-Realism Image Compression with a Conditional Generator, CVPR 2023)
Language:Python 25- Language:Rust 24
tuliopereirab / arithmetic-encoder-av1
This project is being developed as part of a Master's degree research sponsored by Brazil's CNPQ. It's goal is to design a hardware architecture to accelerate the AV1 arithmetic encoder.
Language:Verilog 24FGlazov / Python-rANSCoder
A lightweight rANSCoder meant for rapid prototyping.
Language:Python 18michaelmaniscalco / m99
novel high throughput entropy encoder for BWT data
Language:C++ 13rainerzufalldererste / hypersonic-rANS
Some of the fastest decoding range-based Asymetric Numeral Systems (rANS) codecs for x64
Language:C++ 11- Language:Zig 9
d-becking / efficientCNNs
Finding Storage- and Compute-Efficient Convolutional Neural Networks
Language:Python 7RapidsAtHKUST / DBGC
Source code of "Density-Based Geometry Compression for LiDAR Point Clouds", accepted by EDBT'23 - By Xibo Sun and Prof. Qiong Luo
Language:C++ 7- neurips-2019-micronet-challenge
NeurIPS 2019 MicroNet Challenge
Language:Python 6 - oj-codecLanguage:C++ 5
mpetri / ans-large-alphabet
Large-Alphabet Semi-Static Entropy Coding Via Asymmetric Numeral Systems
Language:C++ 4Abhik35 / Assignment-Decision_Tree-company_data
Assignment About the data: Let’s consider a Company dataset with around 10 variables and 400 records. The attributes are as follows: Sales -- Unit sales (in thousands) at each location Competitor Price -- Price charged by competitor at each location Income -- Community income level (in thousands of dollars) Advertising -- Local advertising budget for company at each location (in thousands of dollars) Population -- Population size in region (in thousands) Price -- Price company charges for car seats at each site Shelf Location at stores -- A factor with levels Bad, Good and Medium indicating the quality of the shelving location for the car seats at each site Age -- Average age of the local population Education -- Education level at each location Urban -- A factor with levels No and Yes to indicate whether the store is in an urban or rural location US -- A factor with levels No and Yes to indicate whether the store is in the US or not The company dataset looks like this: Problem Statement: A cloth manufacturing company is interested to know about the segment or attributes causes high sale. Approach - A decision tree can be built with target variable Sale (we will first convert it in categorical variable) & all other variable will be independent in the analysis.
Language:Jupyter Notebook 3- Language:Rust 3
- Language:Python 2
jermp / entropy_coding
Some entropy coding algorithms in C++.
Language:C++ 2mieskolainen / RLS-Golomb-Rice
RLS-Golomb-Rice lossless codec (TUT course project)
Language:Matlab 2AbhishekSalian / Shannon-Fano-Coding
This program is created to understand how Shannon Fano Coding works.
Language:Jupyter Notebook 1This repository is for reproducing the results shown in the NNCodec ICML Workshop paper. Additionally, it includes a demo, prepared for the Neural Compression Workshop (NCW).
Language:Python 1Junaidk11 / golomb_code
Studying the efficiency of Golomb Coding for geometric distribution.
Language:MATLAB 1mayank-k-jha / Information-Theory-Message-Entropy-Probability
Analog and digital Communication - Information Theory - Message Probability & Entropy
Language:Python 1RadjaaLarbi / Arithmetic-Code
Arithmetic Coding for Data Compression
Language:C++ 1respinha / audio-video-codification
Assignments for the Audio Video Codification course.
Language:C++ 1username1565 / incompressible_data
Try to compress incompressible data
Language:Python 1- Language:Python 1
duanzhiihao / ans-numpy
Fast python bindings for Asymmetric Numeral Systems (ported from ryg_rans). Supports CompressAI models.
Language:Jupyter Notebook 0MirandaDataScience / PokemonEntropy
Um estudo sobre entropia dos dados, o intuito é saber a variabilidade dos dados que possui muitas classe para isso foi aplicado a tipos de pokemons.
Language:Python 0
