Here are
20 public repositories
matching this topic...
Updated
Jul 23, 2020
Jupyter Notebook
AIMET is a library that provides advanced quantization and compression techniques for trained neural network models.
Updated
Aug 11, 2020
Python
Official PyTorch implementation of "A Comprehensive Overhaul of Feature Distillation" (ICCV 2019)
Updated
Jun 23, 2020
Python
Knowledge Transfer via Distillation of Activation Boundaries Formed by Hidden Neurons (AAAI 2019)
Updated
Sep 9, 2019
Python
Knowledge Distillation with Adversarial Samples Supporting Decision Boundary (AAAI 2019)
Updated
Sep 9, 2019
Python
MUSCO: MUlti-Stage COmpression of neural networks
Updated
May 27, 2020
Jupyter Notebook
Group Sparsity: The Hinge Between Filter Pruning and Decomposition for Network Compression. CVPR2020.
Updated
Apr 30, 2020
Python
This is the official implementation of "DHP: Differentiable Meta Pruning via HyperNetworks".
Neural Network Quantization & Low-Bit Fixed Point Training For Hardware-Friendly Algorithm Design
Deep Neural Network Compression based on Student-Teacher Network
Updated
Jun 17, 2019
Python
Pytorch implemenation of "Learning Filter Basis for Convolutional Neural Network Compression" ICCV2019
Updated
Apr 30, 2020
Python
MUSCO: Multi-Stage COmpression of neural networks
Updated
Oct 27, 2019
Python
Updated
Jun 12, 2020
Jupyter Notebook
Updated
Mar 9, 2019
Python
Homework for Machine Learning (2019, Spring) at NTU
Updated
Aug 16, 2019
Python
Updated
Mar 5, 2019
Jupyter Notebook
collection of works aiming at reducing model sizes or the ASIC/FPGA accelerator for machine learning
AIMET GitHub pages documentation
Updated
Jun 14, 2020
HTML
Deep Compression on AlexNet
Updated
May 7, 2018
Python
This repository consists of application of Deep Learning Models like DNN, CNN (1D and 2D), RNN (LSTM and GRU) and Variational Autoencoders written from scratch in tensorflow.
Updated
Jun 16, 2019
Jupyter Notebook
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