MXHX7199

SNN-SSTDP

SSTDP is a efficient spiking neural network training framework, which is contributed by Fangxin Liu and Wenbo Zhao.

ICCV_2021_AFP

AFP is a hardware-friendly quantization framework for DNNs, which is contributed by Fangxin Liu and Wenbo Zhao.

SearchPaper

The articles related to quantization

MXHX7199.github.io

Fangxin Liu's home page

SIGIR22-EnsembleHDC

L3E-HDC is a framework by ensembling HDC for the language task, which is contributed by Fangxin Liu and Haomin Li.

CoLA_Sentence_Classification_BERT

BERT with the huggingface PyTorch library on CoLA dataset for sentence classification and evaluate predictions using Matthew's correlation coefficient

DeepHash-Papers

Must-read papers on deep learning to hash (DeepHash)

gakg

GAKG is a multimodal Geoscience Academic Knowledge Graph (GAKG) framework by fusing papers' illustrations, text, and bibliometric data.

PicGO

S4NN

Temporal backpropagation for spiking neural networks with one spike per neuron, by S. R. Kheradpisheh and T. Masquelier, International Journal of Neural Systems (2020), doi: 10.1142/S0129065720500276

template-weekly-report

Template for a simple weekly report using the markdown syntax

SRCNN-Tensorflow

Image Super-Resolution Using Deep Convolutional Networks in Tensorflow https://arxiv.org/abs/1501.00092v3

vision

Datasets, Transforms and Models specific to Computer Vision