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thu-ml avatar

thu-ml/IODF

0
View on GitHub↗
20 stars·2 forks·C++·MIT·8 views

IODF

This repository contains Pytorch implementation of experiments from the paper Fast Lossless Neural Compression with Integer-Only Discrete Flows. The implementation is based on Integer Discrete Flows. rANS entropy coding in C language is based on local bits back.

Features

  • Filter Pruning - Fast lossless neural compression with integer-only discrete flows.

Star history

Star history chart for thu-ml/iodfStar history chart for thu-ml/iodf

How this analysis was created: This summary and feature list are AI-generated from collected project material and can contain mistakes. Stars, license and language are imported from GitHub. Inclusion does not mean that we have tested or audited this project. Check the source documentation for any feature you depend on. Learn more on our About page.

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Projects sharing features with IODF

These projects share indexed features with IODF. Shared tags can include platform or build tooling; verify the primary use case before treating a result as a replacement.
  • arthurwalraven/cnnslthArthurWalraven avatar

    ArthurWalraven/cnnslth

    1View on GitHub↗

    This is the code used to produce the empyrical results reported in our paper.

    Julia
    View on GitHub↗1
  • bernardo1998/fairgrapeBernardo1998 avatar

    Bernardo1998/FairGRAPE

    18View on GitHub↗

    This repo presents an official implementation of FairGRAPE: Fairness-aware GRAdient Pruning mEthod for Face Attribute Classification

    Python
    View on GitHub↗18
  • boschresearch/sospboschresearch avatar

    boschresearch/sosp

    1View on GitHub↗

    Official PyTorch implementation of the paper "SOSP: Efficiently Capturing Global Correlations by Second-Order Structured Pruning"

    View on GitHub↗1
  • alii-ganjj/interpretationssteeredpruningAlii-Ganjj avatar

    Alii-Ganjj/InterpretationsSteeredPruning

    5View on GitHub↗

    This repository contains the official PyTorch implementation for the paper:

    View on GitHub↗5
Compare all 30 related projects→

Frequently asked questions

What does thu-ml/iodf do?

This repository contains Pytorch implementation of experiments from the paper Fast Lossless Neural Compression with Integer-Only Discrete Flows. The implementation is based on Integer Discrete Flows. rANS entropy coding in C language is based on local bits back.

What are the main features of thu-ml/iodf?

The main features of thu-ml/iodf are: Filter Pruning.

Which projects share features with thu-ml/iodf?

Projects with overlapping indexed features include: arthurwalraven/cnnslth — This is the code used to produce the empyrical results reported in our paper. bernardo1998/fairgrape — This repo presents an official implementation of FairGRAPE: Fairness-aware GRAdient Pruning mEthod for Face Attribute… boschresearch/sosp — Official PyTorch implementation of the paper "SOSP: Efficiently Capturing Global Correlations by Second-Order… dingxiaoh/resrep — State-of-the-art channel pruning (a.k.a. filter pruning)! This repo contains the code for ResRep: Lossless CNN Pruning… eric-mingjie/network-slimming — Network Slimming (Pytorch) (ICCV 2017). alii-ganjj/interpretationssteeredpruning — This repository contains the official PyTorch implementation for the paper:.