Efficient computing methods developed by Huawei Noah's Ark Lab
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Updated
Apr 8, 2024 - Jupyter Notebook
Efficient computing methods developed by Huawei Noah's Ark Lab
(New version is out: https://github.com/hpi-xnor/BMXNet-v2) BMXNet: An Open-Source Binary Neural Network Implementation Based on MXNet
BinaryNets in TensorFlow with XNOR GEMM op
BMXNet 2: An Open-Source Binary Neural Network Implementation Based on MXNet
Binary Neural Network Framework for FPGA(Differentiable LUT)
Pytorch implementation of our paper accepted by NeurIPS 2020 -- Rotated Binary Neural Network
System Verilog code describing a fully combinational binarized neural network.
Implemented here a Binary Neural Network (BNN) achieving nearly state-of-art results but recorded a significant reduction in memory usage and total time taken during training the network.
This project is the official implementation of our accepted ICLR 2021 paper BiPointNet: Binary Neural Network for Point Clouds.
The collection of training tricks of binarized neural networks.
[CVPRW 21] "BNN - BN = ? Training Binary Neural Networks without Batch Normalization", Tianlong Chen, Zhenyu Zhang, Xu Ouyang, Zechun Liu, Zhiqiang Shen, Zhangyang Wang
S2-BNN: Bridging the Gap Between Self-Supervised Real and 1-bit Neural Networks via Guided Distribution Calibration (CVPR 2021)
Binary neural networks developed by Huawei Noah's Ark Lab
PyTorch implementation of Local Binary Convolutional Neural Network http://xujuefei.com/lbcnn.html
PyTorch implementation of binary neural networks
Pytorch implementation of BiFSMNv2, TNNLS 2023
Tricks for Accelerating (encrypted) Prediction As a Service
[ICCV 2021] Code release for "Sub-bit Neural Networks: Learning to Compress and Accelerate Binary Neural Networks"
Proximal Mean-field for Neural Network Quantization
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