bnn

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、regular and group convolutional channel pruning; 3、 group convolution structure; 4、batch-normalization fuse for quantization. deploy: tensorrt, fp32/fp16/int8(ptq-calibration)、op-adapt(upsample)、dynamic_shape

PyTorch-based library for Riemannian Manifold Hamiltonian Monte Carlo (RMHMC) and inference in Bayesian neural networks

The collection of training tricks of binarized neural networks.

Bayesian Neural Network in 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"

HLS code for a BNN accelerator

Neural Property Approximate Quantifier

This is a framework for binary neural network based mmclassification

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

Awesome papers on Neural Networks and Deep Learning

Bayesian Neural Networks with Parallelized Sampling of LogLikelihood

A set of ML algorithms focused on low-end hardware with bit neural networks.

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

Handwritten numbers predicted by bit neural networks

An implementation of the Binarized Neural Networks

Binarized Neural Networks in Pytorch with custom CUDA XNOR kernel

How Alien AI Runs A Human Host.

Multi-omics classification on kidney samples exploiting uncertainty-aware models

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

Age Estimation

Pred on Stock Index

Quantize weights and activations in Recurrent Neural Networks.

Collection of my R&D works and implementations in my Airbus Master Thesis

Exploring the link between uncertainty estimates obtained via "exact" Bayesian inference and out-of-distribution (OOD) detection.

A Keras code on Binary Neural Networks

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

Here are some notes of learning and common codes