canghaiwuya Goto Github PK

acon

Official Repsoitory for "Activate or Not: Learning Customized Activation." [CVPR 2021]

adversarial-reweighting-for-partial-domain-adaptation

Code for Adversarial Reweighting for Partial Domain Adaptation (NeurIPS 2021)

agnn

Code for paper "Attentive Graph Neural Networks for Few-shot Learning"

arpm

Code for ARPM ("Adversarial Reweighting with α-Power Maximization: A Theoretically Motivated Approach for Partial Domain Adaptation")

awesome-domain-adaptation

域自适应图像分类

bnm

code of Towards Discriminability and Diversity: Batch Nuclear-norm Maximization under Label Insufficient Situations (CVPR2020 oral)

capsgnn

胶囊图神经网络

cdan

Code release for "Conditional Adversarial Domain Adaptation" (NIPS 2018)

cgdm

Codes for "Cross-Domain Gradient Discrepancy Minimization for Unsupervised Domain Adaptation" in CVPR 2021

cqu_thesis2024

重庆大学毕业论文Latex模板（修改版）

cquthesis

:pencil: 重庆大学毕业论文LaTeX模板---LaTeX Thesis Template for Chongqing University

csr

code of paper "Cycle Self-Refinement for Multi-source Domain Adaptation"

cst-gl

Multivariate Time-Series Anomaly Detection with GNN.

deep-unsupervised-domain-adaptation

Pytorch implementation of four neural network based domain adaptation techniques: DeepCORAL, DDC, CDAN and CDAN+E. Evaluated on benchmark dataset Office31.

dlwcb

基于Laplace小波卷积和BiGRU的少量样本故障诊断方法 (Small sample fault diagnosis based on Laplace wavelet convolution and BiGRU)

ecb

[CVPR2024] Learning CNN on ViT: A Hybrid Model to Explicitly Class-specific Boundaries for Domain Adaptation

evt

使用极端值理论(Extreme Value Theory)实现阈值动态自动化设置

gnn_fd

基于图神经网络的机械故障诊断

gramian-angular-field-in-pytorch

A implementation of Gramian Angular Field (GAF) in Pytorch.

hustbearing-dataset

This reposotory release a bearing failure dataset, which can support intelliegnt fault diagnosis research（实验室自采轴承开源数据集）

ila-da

improving-few-shot-learning-across-domains-

A novel cross-domain few-shot learning framework leveraging Domain Adaptation Transformer (DAT) and Graph Neural Network (GNN) for improved accuracy in adapting models from a source domain to a target domain, surpassing existing benchmarks on Office and CropDisease datasets.

install

一键安装程序，欢迎大家提交代码和小鱼一起一键安装停止浪费生命

jdda

Code for the paper "Joint Domain Alignment and Discriminative Feature Learning for Unsupervised Deep Domain Adaptation" (AAAI-2019)

jdda-master

Joint Domain Alignment and Discriminative Feature Learning for Unsupervised Deep Domain Adaptation（AAAI-2019）

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

mabn

maximum-mean-square-discrepancy

Maximum mean square discrepancy: A new discrepancy representation metric for mechanical fault transfer diagnosis

mcd_da

最大识别器差异度量算法

mekt

Manifold Embedded Knowledge Transfer for Brain-Computer Interfaces (MEKT)