Compression algorithms techniques: LZ77, LZW, Standard Huffman, Adaptive Humman, quantizer, and predictive feed forward
-
Updated
Feb 10, 2018 - Java
Compression algorithms techniques: LZ77, LZW, Standard Huffman, Adaptive Humman, quantizer, and predictive feed forward
Models made for Edge Devices and NN Optimizations
This package is for one dimensional signal processing, converting time domain signals into frequency components, and additional operations that help in preprocessing the signals
DynamicQuantization_Bert from pytorch tutorials
A toy example of OCTAV algorithm for finding the optimal clipping scalar in the quantization error problem
[EACL 2023 main] This Repository provides a Pytorch implementation of Teacher Intervention: Improving Convergence of Quantization Aware Training for Ultra-Low Precision Transformers
Quantization and pruning methods for model optimization during inference
Implementation of SOMs (Self-Organizing Maps) with neighborhood-based map topologies.
Adaptive Message Quantization and Parallelization for Distributed Full-graph GNN Training
A Fully Quantized SSM Implementation
Regularized Classification-Aware Quantization
code for paper: https://arxiv.org/pdf/2203.08080.pdf
Repo destined for the audience of GDG IOTMakers' program, this workshop goes throught the basics of converting Tensorflow models into TFlite ones and experimenting with different compression and optimization techniques.
Basic algorithms and methods in computer vision
A compilation of various ML and DL models and ways to optimize the their inferences.
Optimizing quantization tables for JPEG2000 codec with significant rate-accuracy performance.
Add a description, image, and links to the quantization topic page so that developers can more easily learn about it.
To associate your repository with the quantization topic, visit your repo's landing page and select "manage topics."