Popular GitHub Repositories for Mi Pyt

A Python library for adversarial machine learning focusing on benchmarking adversarial robustness.

《照片修复小小助手》是一款基于微信AI能力的微信小程序，实现了图片选定区域的消除修复功能，纯客户端实现，无服务端。Inpaint_wechat is a WeChat mini-program based on the WeChat AI capabilities, implementing the functionality of inpainting and repairing selected areas in images, which is purely implemented by the client and has no server.

CTNet: A Convolutional Transformer Network for EEG-Based Motor Imagery Classification

A new approach based on a 10-layer one-dimensional convolution neural network (1D-CNN) to classify five brain states (four MI classes plus a 'baseline' class) using a data augmentation algorithm and a limited number of EEG channels. Paper: https://doi.org/10.1088/1741-2552/ac4430

A curated collection of resources focused on the Mechanistic Interpretability (MI) of Large Multimodal Models (LMMs). This repository aggregates surveys, blog posts, and research papers that explore how LMMs represent, transform, and align multimodal information internally.

This repository contains the implementation of three adversarial example attack methods FGSM, IFGSM, MI-FGSM and one Distillation as defense against all attacks using MNIST dataset.

AMD OpenVX modules: such as, neural network inference, 360 video stitching, etc.

Implementation of gradient-based adversarial attack(FGSM,MI-FGSM,PGD)

The ChatGPT/DeepSeek Voice Assistant uses a Raspberry Pi (or desktop) to enable spoken conversation with OpenAI or DeepSeek large language models. This implementation listens to speech, processes the conversation through the OpenAI/DeepSeek service, and responds back. Like Apple Siri, Amazon Alex, Google Nest Home, Mi XiaoAi etc.

A research repository of deep learning on electroencephalographic (EEG) for Motor imagery(MI), including eeg data processing(visualization & analysis), papers(research and summary), deep learning models(reproduction and experiments).

[ACM MobiCom 2022] "PyramidFL: Fine-grained Data and System Heterogeneity-aware Client Selection for Efficient Federated Learning" by Chenning Li, Xiao Zeng, Mi Zhang, and Zhichao Cao.

[NeurIPS 2022] "FedRolex: Model-Heterogeneous Federated Learning with Rolling Sub-Model Extraction" by Samiul Alam, Luyang Liu, Ming Yan, and Mi Zhang

[NeurIPS 2020] "Does Unsupervised Architecture Representation Learning Help Neural Architecture Search?" by Shen Yan, Yu Zheng, Wei Ao, Xiao Zeng, Mi Zhang

[SenSys 2021] "NELoRa: Towards Ultra-low SNR LoRa Communication with Neural-enhanced Demodulation" by Chenning Li, Hanqing Guo, Shuai Tong, Xiao Zeng, Zhichao Cao, Mi Zhang, Qiben Yan, Li Xiao, Jiliang Wang, Yunhao Liu

This is a deep learning based library for handling Turkish clitics such as da, de, ki and mi.

Dota 2 Match Result Predictor Telegram Bot Overview This project is a Telegram bot that leverages a XGBoost neural network model to predict the outcomes of Dota 2 matches. The bot provides users with real-time predictions based on current match data, making it a useful tool for Dota 2 enthusiasts and analysts.

mi-optimize is a versatile tool designed for the quantization and evaluation of large language models (LLMs). The library's seamless integration of various quantization methods and evaluation techniques empowers users to customize their approaches according to specific requirements and constraints, providing a high level of flexibility.

Classifier for detection and prediction of the type of MI or NORM from 12-lead ECG beats.

IJCAI 2022 Long Presentation: An inductive KG link prediction utilizing neighboring relations from two aspects and using the MI maximization.

[ICML 2021 Oral] "CATE: Computation-aware Neural Architecture Encoding with Transformers" by Shen Yan, Kaiqiang Song, Fei Liu, Mi Zhang