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followers: 11.0 following: 18.0 repos: 66.0 gists: 0.0

Name: Su Yanchi

Type: User

Company: Jilin University

Bio: Ph.D. student of Jilin University

Su Yanchi's Projects

gpu-fish

A parallel framework for matrix completion.

hsi-sdecnn

Source code of "A Single Model CNN for Hyperspectral Image Denoising"

hyperspectral-image-denoising-benchmark

A list of hyperspectral image denoising resources collected by Yongsen Zhao and Junjun Jiang.

igmc

Inductive graph-based matrix completion (IGMC) from "M. Zhang and Y. Chen, Inductive Matrix Completion Based on Graph Neural Networks, ICLR 2020 spotlight".

image-smoothing-state-of-the-art

Image Smoothing: State-of-the-art

leoatchina-datasci

基于rstudio、code-server、jupyter-lab的dockerfile，用于快速搭建数据分析环境。

lrslibrary

Low-Rank and Sparse Tools for Background Modeling and Subtraction in Videos

mdmisc_notes

Links to all data science, genomics, and other notes

nlp-phd-global-equality

A repo for open resources & information for people to succeed in PhD in CS & career in AI / NLP

nmflibrary

MATLAB library for non-negative matrix factorization (NMF): Version 1.8.0

pythondatasciencehandbook

Python Data Science Handbook: full text in Jupyter Notebooks

pytorch-tutorial

PyTorch Tutorial for Deep Learning Researchers

r-color-palettes

Comprehensive list of color palettes available in r ❤️🧡💛💚💙💜

regularized-matrix-completion

Regularized Matrix Completion with Partial Side Information

scatac-seq_notes

scATAC-seq data analysis tools and papers

scrna-tools

Table of software for the analysis of single-cell RNA-seq data.

scrna.seq.course

Analysis of single cell RNA-seq data course

scwmc

Source code of "scWMC: weighted matrix completion-based imputation of scRNA-seq data via prior subspace information"

singan

Official pytorch implementation of the paper: "SinGAN: Learning a Generative Model from a Single Natural Image"

spgl1

A solver for large-scale sparse reconstruction

starter-academic

🎓 Easily create a beautiful academic résumé or educational website using Hugo, GitHub, and Netlify

state-of-the-art-result-for-machine-learning-problems

This repository provides state of the art (SoTA) results for all machine learning problems. We do our best to keep this repository up to date. If you do find a problem's SoTA result is out of date or missing, please raise this as an issue or submit Google form (with this information: research paper name, dataset, metric, source code and year). We will fix it immediately.

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