1615405

LogicStack-LeetCode

公众号「宫水三叶的刷题日记」刷穿 LeetCode 系列文章源码

ESM-GearNet

ESM-GearNet for Protein Structure Representation Learning (https://arxiv.org/abs/2303.06275)

GearNet

GearNet and Geometric Pretraining Methods for Protein Structure Representation Learning, ICLR'2023 (https://arxiv.org/abs/2203.06125)

ATOMRefine

3D equivariant graph transformer for all-atom refinement of protein tertiary structures

esm-AxP-GDL

MMCD

alphafold2

To eventually become an unofficial Pytorch implementation / replication of Alphafold2, as details of the architecture get released

CSAPP-Notes

CSAPP Notes

bilibili_sentiment_analysis

B站的弹幕的获取，情感分析和词云图

sentiment-analysis

情感分析、文本分类、词典、bayes、sentiment analysis、TextCNN、classification、tensorflow、BERT、CNN、text classification

chinese_sentiment

中文情感分析，CNN，BI-LSTM，文本分类

SPAM_CLASSIFY_online

一个垃圾短信识别系统——国科大网络数据挖掘(徐君)课程设计

HanLP

中文分词 词性标注 命名实体识别 依存句法分析 成分句法分析 语义依存分析 语义角色标注 指代消解 风格转换 语义相似度 新词发现 关键词短语提取 自动摘要 文本分类聚类 拼音简繁转换 自然语言处理

data-mining-course

数据挖掘作业

Porter5

Fast, state-of-the-art ab initio prediction of protein secondary structure in 3 and 8 classes

ac-library-python

NIMGSA

Predicting miRNA–disease association based on neural inductive matrix completion with graph autoencoders and self-attention mechanism

CKG-IMC

CKG-IMC: an inductive matrix completion method enhanced by collaborative knowledge graph and graph neural network for Alzheimer’s disease compound-protein interactions prediction

GATMDA

Predicting miRNA-disease associations based on graph attention network with multi-source information

COLA

Chinese-Word-Vectors

100+ Chinese Word Vectors 上百种预训练中文词向量

wordcloud

生成词云图

wide-residual-networks

3.8% and 18.3% on CIFAR-10 and CIFAR-100

MVGAEW

Vanilla-RNN

Vanilla RNN classification with pytorch on AG_NEWS dataset.

python-special-efficiency

🌈Python特效实战：词云表白、图片转字符画、图片转数字画、千图成像、数字舞蹈、可视化进度条、无穷炫酷五角星、黑客帝国代码雨、无法关闭的表白弹窗、一行代码能实现的丧心病狂的功能、图片特效转换、高级图片特效处理、3d图片渲染等

cpp-qt-manageSystem

WTU课设基于C++和qt的超市商品管理系统

Graphics-Library

Download required libraries from here

c_AMPs-prediction

following-instructions-human-feedback