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[CVPR 2023] DepGraph: Towards Any Structural Pruning
A curated list of neural network pruning resources.
Code for our paper at ECCV 2020: Post-Training Piecewise Linear Quantization for Deep Neural Networks
alibabacloud-quantization-networks
Quantization of Convolutional Neural networks.
Rethinking the Value of Network Pruning (Pytorch) (ICLR 2019)
Channel Pruning for Accelerating Very Deep Neural Networks (ICCV'17)
A repository for storing models that have been inter-converted between various frameworks. Supported frameworks are TensorFlow, PyTorch, ONNX, OpenVINO, TFJS, TFTRT, TensorFlowLite (Float32/16/INT8…
Facebook AI Research Sequence-to-Sequence Toolkit written in Python.
Summary, Code for Deep Neural Network Quantization
Papers for deep neural network compression and acceleration
a list of awesome papers on deep model ompression and acceleration
micronet, a model compression and deploy lib. compression: 1、quantization: quantization-aware-training(QAT), High-Bit(>2b)(DoReFa/Quantization and Training of Neural Networks for Efficient Integer-…
Quantized Neural Network PACKage - mobile-optimized implementation of quantized neural network operators
A toolkit to optimize ML models for deployment for Keras and TensorFlow, including quantization and pruning.
KITTI Object Visualization (Birdview, Volumetric LiDar point cloud )
Python tools for working with KITTI data.
🎨 ML Visuals contains figures and templates which you can reuse and customize to improve your scientific writing.
PyTorch implementation of 'Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding' by Song Han, Huizi Mao, William J. Dally
B站Efficient-Neural-Network学习分享的配套代码
End-to-End Object Detection with Transformers
[ICML 2019] Circuit-GNN: Graph Neural Networks for Distributed Circuit Design http://circuit-gnn.csail.mit.edu/
Code for paper " AdderNet: Do We Really Need Multiplications in Deep Learning?"