chatgpt问答微信小程序，chatAI-MP是基于TP5+Uniapp+VUE开发，基于各大AI大语言模型API实现的AI助手开源解决方案，已集成ChatGPT、文心一言、通义千问、360智脑、ChatGLM（清华旗下）、讯飞星火等人工智能技术，开源版支持PC、微信小程序等多端，微信接口安全审核机制。部署后即为SAAS系统，可无限搭建小程序、PC平台。

小飞薯RPA是一款紧贴小红书优质用户规则开发的自动化运营软件

Respiratory Modulation with Morphological Autoencoders for Anomaly Detection. Experiments with two datasets (sleep apnea and breathing exercises).

基于电生理信号与深度学习 的睡眠障碍诊断分析与研究

Driver drowsiness is one of the causes of traffic accidents. According to the statistics; highway road crashes hold 11.09% of the total number of accidents. There are several reasons of drowsy driv…

Code for IEEE Communication Magazine (A Survey on Behaviour Recognition Using WiFi Channle State Information)

Human Activity Recognition using Channel State Information

数据挖掘、计算机视觉、自然语言处理、推荐系统竞赛知识、代码、思路

A syntactic neural model for parsing natural language to executable code

Large Language Models Meet NL2Code: A Survey

Robust machine learning for responsible AI

source code of AAAI 2024 paper "Graph Invariant Learning with Subgraph Co-mixup for Out-Of-Distribution Generalization".

关于domain generalization，domain adaptation，causality，robutness，prompt，optimization，generative model各式各样研究的阅读笔记

wind_power_forecast

KDD Cup 2022 spatial dynamic wind power forecast challenge solution.

Data processing for and with foundation models! 🍎 🍋 🌽 ➡️ ➡️🍸 🍹 🍷

[KDD 2022] "Causal Attention for Interpretable and Generalizable Graph Classification" by Yongduo Sui, Xiang Wang, Jiancan Wu, Min Lin, Xiangnan He, Tat-Seng Chua.

Toolkit for building machine learning models that generalize to unseen domains and are robust to privacy and other attacks.

为GPT/GLM等LLM大语言模型提供实用化交互接口，特别优化论文阅读/润色/写作体验，模块化设计，支持自定义快捷按钮&函数插件，支持Python和C++等项目剖析&自译解功能，PDF/LaTex论文翻译&总结功能，支持并行问询多种LLM模型，支持chatglm3等本地模型。接入通义千问, deepseekcoder, 讯飞星火, 文心一言, llama2, rwkv, claude2, m…

GOOD: A Graph Out-of-Distribution Benchmark [NeurIPS 2022 Datasets and Benchmarks]

bloop is a fast code search engine written in Rust.

[SOTA results in GOOD benchmark🚀] CIGA Implementation under GOOD Benchamrk

[ICML 2022] Graph Stochastic Attention (GSAT) for interpretable and generalizable graph learning.

[KDD'22] Source codes of "Graph Rationalization with Environment-based Augmentations"

Papers about out-of-distribution generalization on graphs.

[NN 2024] Towards Generalizable Graph Contrastive Learning: An Information Theory Perspective

A list of Graph Causal Learning materials.

[NeurIPS 2022] Learning Causally Invariant Representations for Out-of-Distribution Generalization on Graphs

ChatGPT 中文调教指南。各种场景使用指南。学习怎么让它听你的话。