Efficient computing methods developed by Huawei Noah's Ark Lab
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Updated
Nov 5, 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
BMXNet 2: An Open-Source Binary Neural Network Implementation Based on MXNet
BinaryNets in TensorFlow with XNOR GEMM op
Binary Neural Network Framework for FPGA(Differentiable LUT)
This project is the official implementation of 'Basic Binary Convolution Unit for Binarized Image Restoration Network', ICLR2023
Pytorch implementation of our paper accepted by NeurIPS 2020 -- Rotated Binary Neural 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.
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.
S2-BNN: Bridging the Gap Between Self-Supervised Real and 1-bit Neural Networks via Guided Distribution Calibration (CVPR 2021)
[CVPRW 21] "BNN - BN = ? Training Binary Neural Networks without Batch Normalization", Tianlong Chen, Zhenyu Zhang, Xu Ouyang, Zechun Liu, Zhiqiang Shen, Zhangyang Wang
[ICML 2023] This project is the official implementation of our accepted ICML 2023 paper BiBench: Benchmarking and Analyzing Network Binarization.
PyTorch implementation of Local Binary Convolutional Neural Network http://xujuefei.com/lbcnn.html
PyTorch implementation of binary neural networks
BITorch: Open-Source Implementation of Binary Neural Networks with PyTorch
System Verilog code describing a fully combinational binarized neural network.
[ICCV 2021] Code release for "Sub-bit Neural Networks: Learning to Compress and Accelerate Binary Neural Networks"
Binary neural networks developed by Huawei Noah's Ark Lab
Pytorch implementation of BiFSMNv2, TNNLS 2023
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