## https://www.slideserve.com/darleneandre/deep-neural-network-optimization-binary-neural-networks-powerpoint-ppt-presentation

## Software approaches

## algorithms

- 2016 [Binarized Neural Networks: Training Deep Neural Networks with Weights and Activations Constrained to +1 or -1](https://arxiv.org/abs/1602.02830) Matthieu Courbariaux

## [Quantized Neural Networks: Training Neural Networks with Low Precision Weights and Activations](https://arxiv.org/abs/1609.07061) Itay Hubara, Matthieu Courbariaux

- 2020 [Controlling Information Capacity of Binary Neural Network](https://arxiv.org/abs/2008.01438) Dmitry Ignatov, Andrey Ignatov


## Hardware approaches

2018 [XNOR Neural Engine: a Hardware Accelerator IP for 21.6 fJ/op Binary Neural Network Inference](https://arxiv.org/abs/1807.03010)


## +++  **2018 Stanford** [An Always-On 3.8 μJ/86% CIFAR-10 Mixed-Signal Binary CNN Processor With All Memory on Chip in 28-nm CMOS](https://knowen-production.s3.amazonaws.com/uploads/attachment/file/5083/bankman2018.pdf) Daniel Bankman


## 2020 - Review [An Updated Survey of Efficient Hardware Architectures for Accelerating Deep Convolutional Neural Networks](https://res.mdpi.com/d_attachment/futureinternet/futureinternet-12-00113/article_deploy/futureinternet-12-00113-v2.pdf) Maurizio Capra

![hhhh](https://knowen-production.s3.amazonaws.com/uploads/attachment/file/5297/variable%2Bbitwidth.PNG 'hhh')

## https://larq.dev/

video [tinyML Talks Lukas Geiger: Binarized Neural Networks on microcontrollers](https://www.youtube.com/watch?v=f9SNqDejOB0)

- [short intro about Plumerai](https://apply.workable.com/plumerai/)

[MLSys 2021: Design, Benchmark, and Deploy Binarized Neural Networks with Larq Compute Engine](https://blog.plumerai.com/2021/04/mlsys21/)

## more general

2015 [Memristor-Based Multilayer Neural Networks With Online Gradient Descent Training](https://ieeexplore.ieee.org/document/7010034)