gudovskiy / fmap_compressionLinks
Code for DNN feature map compression paper
☆11Updated 7 years ago
Alternatives and similar repositories for fmap_compression
Users that are interested in fmap_compression are comparing it to the libraries listed below
Sorting:
- I'm going to use the Winograd’s minimal filtering algorithms to introduce a new class of fast algorithms for convolutional neural networks…☆12Updated 7 years ago
- Artifact for IPDPS'21: DSXplore: Optimizing Convolutional Neural Networks via Sliding-Channel Convolutions.☆13Updated 4 years ago
- Codes for AAAI2019 paper: Deep Neural Network Quantization via Layer-Wise Optimization using Limited Training Data☆41Updated 7 years ago
- Pytorch implementation for FAT: learning low-bitwidth parametric representation via frequency-aware transformation☆27Updated 4 years ago
- Implementation of ICLR 2018 paper "Loss-aware Weight Quantization of Deep Networks"☆27Updated 6 years ago
- AutoGrow: Automatic Layer Growing in Deep Convolutional Networks (KDD 2020)☆40Updated 6 years ago
- An adapted version of the original caffe deep learning library to support training, finetuning and testing of convolutional neural networ…☆20Updated 8 years ago
- Proximal Mean-field for Neural Network Quantization☆21Updated 5 years ago
- CAE-ADMM: Implicit Bitrate Optimization via ADMM-Based Pruning in Compressive Autoencoders☆47Updated 5 years ago
- ☆13Updated 6 years ago
- This repo is an implementation of quantized CNN for both weights (1-bit compression) and feature maps (2-bit compression).☆18Updated 7 years ago
- A script to convert floating-point CNN models into generalized low-precision ShiftCNN representation☆57Updated 8 years ago
- Test winograd convolution written in TVM for CUDA and AMDGPU☆41Updated 7 years ago
- Keras implementations of BinaryNet and XNORNet☆55Updated 8 years ago
- ☆17Updated 5 years ago
- Code repositoy for "AOWS: Adaptive and optimal network width search with latency constraints", CVPR 2020☆36Updated 5 years ago
- ☆14Updated 4 years ago
- PyTorch implementation of Near-Lossless Post-Training Quantization of Deep Neural Networks via a Piecewise Linear Approximation☆23Updated 5 years ago
- Deep Compression: Compressing Deep Neural Networks With Pruning, Trained Quantization And Huffman Coding☆16Updated 6 years ago
- Code for the ICLR2020 "Training Binary Neural Networks with Real-to-Binary Convolutions☆34Updated 5 years ago
- The collection of training tricks of binarized neural networks.☆72Updated 4 years ago
- Depth_conv for MobileNet☆30Updated 5 years ago
- This code implements NICE papper☆20Updated 7 years ago
- CNN model inference benchmarks for some popular deep learning frameworks☆52Updated 6 years ago
- HNAS: Hierarchical Neural Architecture Search for Single Image Super-Resolution☆57Updated 5 years ago
- An Example of MXNet Models Comilation and Deployment with NNVM in C++☆16Updated 7 years ago
- This is a PyTorch implementation of the Scalpel. Node pruning for five benchmark networks and SIMD-aware weight pruning for LeNet-300-100…☆41Updated 7 years ago
- Attention-Based Guided Structured Sparsity of Deep Neural Networks☆29Updated 5 years ago
- All about acceleration and compression of Deep Neural Networks☆33Updated 6 years ago
- Keras implementation of the article "Solving internal covariate shift in deep learning with linked neurons"☆13Updated 8 years ago