An Open-Source Library for Training Binarized Neural Networks
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Updated
Apr 29, 2024 - Python
An Open-Source Library for Training 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.
Tools and libraries to run neural networks in Minecraft ⛏️
Reference implementations of popular Binarized Neural Networks
Implementation for the paper "Latent Weights Do Not Exist: Rethinking Binarized Neural Network Optimization"
Some recent Quantizing techniques on PyTorch
This project is the official implementation of our accepted ICML 2023 paper BiBench: Benchmarking and Analyzing Network Binarization.
Contains code for Binary, Ternary, N-bit Quantized and Hybrid CNNs for low precision experiments.
Neural Property Approximate Quantifier
Code implementation of our AISTATS'21 paper "Mirror Descent View for Neural Network Quantization"
An implementation of the Binarized Neural Networks
Progressive Neural Architecture Search coupled with Binarized CNNs to search for resource efficient and accurate architectures.
Code implementation of our AAAI'22 paper "Improved Gradient-Based Adversarial Attacks for Quantized Networks"
The official repository for the paper LAB: Learnable Activation Binarizer for Binary Neural Networks.
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.
A simple deep neural net class written to work with Numpy and Cupy
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