TensorFlow implementation of "Finite Scalar Quantization: VQ-VAE Made Simple" (ICLR 2024)
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Updated
Dec 3, 2023 - Python
TensorFlow implementation of "Finite Scalar Quantization: VQ-VAE Made Simple" (ICLR 2024)
PyTorch implementation of variational entropy-constrained vector quantization.
This repository implements the LZ77, LZ78, Huffman, Vector Quantization, and Arithmetic coding algorithms for data compression and decompression.
A lightweight efficient audio codec in 30MB with 30~170x compression ratio. Supports 16kHz mono speech audio.
PyTorch implementation of 3DQD with modifications (Deep Learning Lab - Uni Freiburg)
VQ-VAE implementation and some experiments.
PyTorch Implementation of Vector Quantized Variational AutoEncoders.
Identifying specific groups in customer base with K-Means clustering
Vector algebra deals with mathematical operations and manipulations involving vectors, which are mathematical objects with both magnitude and direction. Vectors can represent quantities such as forces, velocities, and features in machine learning
A Vector Quantized Masked AutoEncoder for speech emotion recognition
Experiments in neural networks for audio generation.
PyTorch Lightning implementation of the paper Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding. This repository allows to reproduce the main findings of the paper on MNIST and Imagenette datasets.
A Java program that implements Vector Quantization
How can echocardiographic sequences be compressed by using Vector Quantization
naive k-means clustering from scratch in vanilla python
Operating System Algorithms and security Algorithms [AES , DES , ... ] and Multimedia Algorithms [Adaptive Huffman Algorithm, LZ78 , LZ88 , LZW, Vector Quantization Algorithm, ...]
ECOZ2 in Rust
Compression via Vector Quantization in PyTorch
VQ-TensoRF --- Official implementation of our CVPR 2023 paper "Compressing Volumetric Radiance Fields to 1 MB"
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