Pinned Repositories
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Implementation code for the paper "Graph Neural Network-Based Anomaly Detection in Multivariate Time Series" (AAAI 2021)
-PaddleX-
-PALM-5-4-
飞桨常规赛：PALM病理性近视病灶检测与分割 5月第4名方案基线方案
-PALM_project
飞桨常规赛：PALM眼底彩照中黄斑中央凹定位 5月第4名方案
AFGIC
Awesome Fine-Grained Image Classification
AL-based-FL-for-Multi-Task-Disaster-Detection-Model
We design a multi-task model for joint disaster classification and victim detection. We train the model using both the Centralized Learning (CL) and Federated Learning (FL) methods. We also tried Active Learning (AL) to see how it could help in reducing the labeling workload for disaster dataset. Lastly, we optimized the model using OpenVINO.
base_bottom
CNN-based_CWRU_Bearing_Fault_Diagonis
Analysis of CWRU Bearing Data Set and Development of WeChat Mini Program Interface
PaddleRec
大规模推荐模型训练工具
Rotating-machine-fault-data-set
Open rotating mechanical fault datasets (开源旋转机械故障数据集整理)
xiaohongri's Repositories
xiaohongri/-
Implementation code for the paper "Graph Neural Network-Based Anomaly Detection in Multivariate Time Series" (AAAI 2021)
xiaohongri/-PaddleX-
xiaohongri/AFGIC
Awesome Fine-Grained Image Classification
xiaohongri/AL-based-FL-for-Multi-Task-Disaster-Detection-Model
We design a multi-task model for joint disaster classification and victim detection. We train the model using both the Centralized Learning (CL) and Federated Learning (FL) methods. We also tried Active Learning (AL) to see how it could help in reducing the labeling workload for disaster dataset. Lastly, we optimized the model using OpenVINO.
xiaohongri/CNN-based_CWRU_Bearing_Fault_Diagonis
Analysis of CWRU Bearing Data Set and Development of WeChat Mini Program Interface
xiaohongri/CNN-for-Paderborn-Bearing-Dataset
in Python
xiaohongri/deep-learning-for-image-processing
deep learning for image processing including classification and object-detection etc.
xiaohongri/easy-rl
强化学习中文教程（蘑菇书），在线阅读地址：https://datawhalechina.github.io/easy-rl/
xiaohongri/EMO
Emote Portrait Alive: Generating Expressive Portrait Videos with Audio2Video Diffusion Model under Weak Conditions
xiaohongri/ETSformer
PyTorch code for ETSformer: Exponential Smoothing Transformers for Time-series Forecasting 20240317
xiaohongri/FedEM
Official code for "Federated Multi-Task Learning under a Mixture of Distributions" (NeurIPS'21)
xiaohongri/FEDformer
20240317
xiaohongri/GCformer
xiaohongri/HarmoFL
[AAAI'22] HarmoFL: Harmonizing Local and Global Drifts in Federated Learning on Heterogeneous Medical Images
xiaohongri/ImageBind
ImageBind One Embedding Space to Bind Them All
xiaohongri/ImageProcessing-Python
该资源为作者在CSDN的撰写Python图像处理文章的支撑，主要是Python实现图像处理、图像识别、图像分类等算法代码实现，希望该资源对您有所帮助，一起加油。
xiaohongri/Limited-Data-Rolling-Bearing-Fault-Diagnosis-with-Few-shot-Learning
This is the corresponding repository of paper Limited Data Rolling Bearing Fault Diagnosis with Few-shot Learning
xiaohongri/mamba
Mamba SSM architecture
xiaohongri/MTFL-For-Personalised-DNNs
Code for 'Multi-Task Federated Learning for Personalised Deep Neural Networks in Edge Computing', published in IEEE TPDS.
xiaohongri/paderborn_bearing
Package for preprocessing Paderborn Bearing dataset
xiaohongri/PARL
A high-performance distributed training framework for Reinforcement Learning
xiaohongri/pathformer
20240317
xiaohongri/Remaining-Useful-Life-Estimation-Variational
xiaohongri/RWKV-LM-GPT
RWKV is an RNN with transformer-level LLM performance. It can be directly trained like a GPT (parallelizable). So it's combining the best of RNN and transformer - great performance, fast inference, saves VRAM, fast training, "infinite" ctx_len, and free sentence embedding.
xiaohongri/scaleformer
20240317
xiaohongri/segment-anything-2
The repository provides code for running inference with the Meta Segment Anything Model 2 (SAM 2), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.
xiaohongri/Time-Series-Library
A Library for Advanced Deep Time Series Models.
xiaohongri/TrafficMonitor
这是一个用于显示当前网速、CPU及内存利用率的桌面悬浮窗软件，并支持任务栏显示，支持更换皮肤。
xiaohongri/TranAD
[VLDB'22] Anomaly Detection using Transformers, self-conditioning and adversarial training.
xiaohongri/xiaohongri.github.io