kunglab / branchynet
☆124Updated last year
Related projects ⓘ
Alternatives and complementary repositories for branchynet
- ☆117Updated 5 years ago
- Prune DNN using Alternating Direction Method of Multipliers (ADMM)☆107Updated 4 years ago
- XNOR-Net, with binary gemm and binary conv2d kernels, support both CPU and GPU.☆82Updated 5 years ago
- Pytorch-based early exit network inspired by branchynet☆29Updated last year
- FedNAS: Federated Deep Learning via Neural Architecture Search☆52Updated 3 years ago
- A PyTorch implementation of the iterative pruning method described in Han et. al. (2015)☆40Updated 5 years ago
- Codes for Layer-wise Optimal Brain Surgeon☆75Updated 6 years ago
- Mayo: Auto-generation of hardware-friendly deep neural networks. Dynamic Channel Pruning: Feature Boosting and Suppression.☆114Updated 4 years ago
- ☆213Updated 6 years ago
- DNN quantization with outlier channel splitting☆112Updated 4 years ago
- ☆43Updated 4 years ago
- Learning both Weights and Connections for Efficient Neural Networks https://arxiv.org/abs/1506.02626☆174Updated 2 years ago
- About DNN compression and acceleration on Edge Devices.☆55Updated 3 years ago
- Code example for the ICLR 2018 oral paper☆149Updated 6 years ago
- Code for the signSGD paper☆81Updated 3 years ago
- PyTorch Implementation of Weights Pruning☆184Updated 6 years ago
- 基于提前退出部分样本原理而实现的带分支网络(supported by chainer)☆42Updated 5 years ago
- Partial implementation of paper "DEEP GRADIENT COMPRESSION: REDUCING THE COMMUNICATION BANDWIDTH FOR DISTRIBUTED TRAINING"☆31Updated 4 years ago
- ☆47Updated 4 years ago
- Reducing the size of convolutional neural networks☆112Updated 6 years ago
- Code for SkipNet: Learning Dynamic Routing in Convolutional Networks (ECCV 2018)☆236Updated 5 years ago
- ProxQuant: Quantized Neural Networks via Proximal Operators☆28Updated 5 years ago
- ☆53Updated 5 years ago
- Sparsified SGD with Memory: https://arxiv.org/abs/1809.07599☆56Updated 6 years ago
- vector quantization for stochastic gradient descent.☆33Updated 4 years ago
- Pytorch Implementation using Binary Weighs and activation.Accuracies are comparable .☆41Updated 4 years ago
- [ICLR 2018] Deep Gradient Compression: Reducing the Communication Bandwidth for Distributed Training☆213Updated 4 months ago
- Measuring and predicting on-device metrics (latency, power, etc.) of machine learning models☆66Updated last year
- Implementation for Trained Ternary Network.☆108Updated 7 years ago
- Implementation of BinaryConnect on Pytorch☆36Updated 3 years ago