Quantize weights and activations in Recurrent Neural Networks.

Bayesian Neural Network

A simple deep neural net class written to work with Numpy and Cupy

Bayesian Neural Networks with Parallelized Sampling of LogLikelihood

BNN-to-FPGA framework, written in VHDL and Python

micronet, a model compression and deploy lib. compression: 1、quantization: quantization-aware-training(QAT), High-Bit(>2b)(DoReFa/Quantization and Training of Neural Networks for Efficient Integer-Arithmetic-Only Inference)、Low-Bit(≤2b)/Ternary and Binary(TWN/BNN/XNOR-Net); post-training-quantization(PTQ), 8-bit(tensorrt); 2、 pruning: normal、reg…

An implementation of the Binarized Neural Networks

How Alien AI Runs A Human Host.

This repository shows different Bayesian Neural Networks available for predictive uncertainty.

This is a framework for binary neural network based mmclassification

[ICCV 2021] Code release for "Sub-bit Neural Networks: Learning to Compress and Accelerate Binary Neural Networks"

Towards Accurate Binary Neural Networks via Modeling Contextual Dependencies

BiDet implement

The official repository for the paper LAB: Learnable Activation Binarizer for Binary Neural Networks.

Neural Property Approximate Quantifier

A PyTorch implemenation of real XNOR-popcount (1-bit op) GEMM Linear PyTorch extension support both CPU and CUDA

Binarized Neural Networks in Pytorch with a custom CUDA XNOR kernel

This project is the official implementation of 'Basic Binary Convolution Unit for Binarized Image Restoration Network', ICLR2023

A Toolbox for Binarized Spectral Compressive Imaging (NeurIPS 2023)

Bayesian Neural Network in PyTorch