Olson Fredrick's starred repositories
MaaAssistantArknights
《明日方舟》小助手,全日常一键长草!| A one-click tool for the daily tasks of Arknights, supporting all clients.
Time-Series-Library
A Library for Advanced Deep Time Series Models.
youre-the-os
A game where you are a computer's OS and you have to manage processes, memory and I/O events.
Rotating-machine-fault-data-set
Open rotating mechanical fault datasets (开源旋转机械故障数据集整理)
Clash-for-Windows_Chinese
clash for windows汉化版. 提供clash for windows的汉化版, 汉化补丁及汉化版安装程序
Digital-twin-assisted-imbalanced-fault-diagnosis-framework
一种数字孪生辅助的高度不平衡故障诊断新框架
approachingalmost
Approaching (Almost) Any Machine Learning Problem
Transfer-Learning-Library
Transfer Learning Library for Domain Adaptation, Task Adaptation, and Domain Generalization
Graph-Domain-Adaptaion
PyTorch code for the paper "Curriculum Graph Co-Teaching for Multi-target Domain Adaptation" (CVPR2021)
LearningToCompare_FSL
PyTorch code for CVPR 2018 paper: Learning to Compare: Relation Network for Few-Shot Learning (Few-Shot Learning part)
GPT_API_free
Free ChatGPT API Key,免费ChatGPT API,支持GPT4 API(免费),ChatGPT国内可用免费转发API,直连无需代理。可以搭配ChatBox等软件/插件使用,极大降低接口使用成本。国内即可无限制畅快聊天。
deep-transfer-learning
A collection of implementations of deep domain adaptation algorithms
A-Domain-Adaption-Transfer-Learning-Bearing-Fault-Diagnosis-Model-Based-on-Wide-Convolution-Deep-Neu
Inspired by the idea of transfer learning, a combined approach is proposed. In the method, Deep Convolutional Neural Networks with Wide First-layer Kernel is used to extract features to classify the health conditions.
Conditional-Adversarial-Domain-Generalization-with-Single-Discriminator
Pytorch implementation of the paper: "Conditional Adversarial Domain Generalization With a Single Discriminator for Bearing Fault Diagnosis"
CrossDomainFaultDiagnosis
Repository containing the code for the experiments and examples of my Bachelor Thesis: Cross Domain Fault Detection through Optimal Transport
transferlearning
Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习