An Open-Source Library for Training Binarized Neural Networks
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Updated
May 24, 2024 - Python
An Open-Source Library for Training Binarized Neural Networks
Reference implementations of popular Binarized Neural Networks
A toolbox for spectral compressive imaging reconstruction including MST (CVPR 2022), CST (ECCV 2022), DAUHST (NeurIPS 2022), BiSCI (NeurIPS 2023), HDNet (CVPR 2022), MST++ (CVPRW 2022), etc.
This project is the official implementation of our accepted ICML 2023 paper BiBench: Benchmarking and Analyzing Network Binarization.
This repository contains the python code related to the Master's Thesis. In particular, this code is in charge of setting up the NN and training them, calculating the importance and developing the design procedures for reducing the final logic implementation complexity.
Tools and libraries to run neural networks in Minecraft ⛏️
Neural Property Approximate Quantifier
The official repository for the paper LAB: Learnable Activation Binarizer for Binary Neural Networks.
Code implementation of our AAAI'22 paper "Improved Gradient-Based Adversarial Attacks for Quantized Networks"
An implementation of the Binarized Neural Networks
Code implementation of our AISTATS'21 paper "Mirror Descent View for Neural Network Quantization"
A simple deep neural net class written to work with Numpy and Cupy
Implementation for the paper "Latent Weights Do Not Exist: Rethinking Binarized Neural Network Optimization"
Some recent Quantizing techniques on PyTorch
Contains code for Binary, Ternary, N-bit Quantized and Hybrid CNNs for low precision experiments.
Progressive Neural Architecture Search coupled with Binarized CNNs to search for resource efficient and accurate architectures.
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