liguge

liguge's Stars

• Genesis-Embodied-AI/Genesis

  A generative world for general-purpose robotics & embodied AI learning.

  Language:Python24.7k2315692.2k

• 217heidai/adblockfilters

  去广告合并规则，每8个小时更新一次。

  Language:Python3.9k21124280

• OpenGVLab/DCNv4

  [CVPR 2024] Deformable Convolution v4

  Language:Python61299833

• zhouchenlin2096/Awesome-Spiking-Neural-Networks

  A paper list of spiking neural networks, including papers, codes, and related websites. 本仓库收集脉冲神经网络相关的顶会顶刊论文和代码，正在持续更新中。

  39720033

• i207M/PINNacle

  Codebase for PINNacle: A Comprehensive Benchmark of Physics-Informed Neural Networks for Solving PDEs.

  Language:Python30431046

• AFANOOO/sspan

  16022212

• CHAOZHAO-1/Awsome-Multi-modal-based-PHM

  Awsome-Multi-modal-based PHM （基于多模态的故障诊断和预测）

  52712

• Dolphin-wang/Diff-MTS

  Source codes for the paper "Diff-MTS: Temporal-Augmented Conditional Diffusion-Based AIGC for Industrial Time Series Toward the Large Model Era"

  Language:Python4511

• CHAOZHAO-1/LLM-based-PHM

  This is a reposotory that includes paper about LLM-based fault diagnosis and prognosis. (基于大模型的故障诊断和预测，持续更新)

  44113

• jackielinxiao/PE-LTR

  Language:Python44266

• SIA-IDE/BearLLM

  AAAI 2025: BearLLM: A Prior Knowledge-Enhanced Bearing Health Management Framework with Unified Vibration Signal Representation

  Language:Python44277

• liuzy0708/MCC5-THU-Gearbox-Benchmark-Datasets

  A benchmark fault diagnosis dataset comprises vibration data collected from a gearbox under variable working conditions with intentionally induced faults, encompassing diverse fault severities and types, and various compound faults.

  Language:MATLAB40223

• zhiqan/Random-convolution-layer

  Random convolution layer: An auxiliary method to improve fault diagnosis performance

  Language:Python29117

• wang-fujin/BattNN

  Language:Python22105

• xiaoyiming1999/DG-for-RMFD

  Source codes for the paper "Domain generalization for rotating machinery fault diagnosis: A survey" published in Advanced Engineering Informatics journal

  Language:Python22204

• giabao804/few-shot-mamba

  This is our implemented source code for the paper "SC-MambaFew: Few-shot learning based on Mamba and selective spatial-channel attention for bearing fault diagnosis" published in the Journal of Computers and Electrical Engineering

  Language:Python19113

• ShinanZou/MSAFF

  (MSAFF) A Multi-Stage Adaptive Feature Fusion Neural Network for Multimodal Gait Recognition

  Language:Python19181

• Cloudfly-Z/ACAN

  ACAN: A Plug-and-Play Adaptive Center-Aligned Network for Unsupervised Domain Adaptation

  Language:Python16312

• srigas/KAN_Fault_Diagnosis

  A public repository containing the data and code for the paper "Explainable fault and severity classification for rolling element bearings using Kolmogorov-Arnold networks".

  Language:Python13112

• Lqj-creator/MMCL-for-Fault-Diagnosis

  We propose a novel semi-supervised learning framework for fault diagnosis in scenarios with limited labeled data, using a Multiscale and Multilevel Contrastive Learning (MMCL) approach.

  Language:Python11100

• freshman-ip/PINN

  用于求解薛定谔方程的数值解

  Language:Python1010

• KWflyer/WTFF

  Wide Kernel Time-Frequency Fusion （WTFF）--Multi-Domain Time-Frequency Fusion Feature Contrastive Learning for Machinery Fault Diagnosis

  Language:Python9

• zimufengyan/MMPN-FD

  The source code (Pytorch version) of paper "Multi-modality augmented Prototypical Network for Fault Diagnosis"

  Language:Python9111

• ChenQian0618/CS-SHAP

  The open-source code of "CS-SHAP: Extending SHAP to Cyclic-Spectral Domain for Better Interpretability of Intelligent Fault Diagnosis".

  7100

• N-JIA-NJ/PIUDA

  Language:MATLAB510

• CQU-BITS/FIR-CCF-main

  The implementation of knowledge-informed FIR-based Cross-category Filtering (FIR-CCF) framework in Pytorch.

  Language:Python4

• ChengjiaHanSEU/Transfer-AE

  Language:Jupyter Notebook3100

• GuoweiaaZhang/ADC

  ADC

  30

• nmahamoodally/Transfer-Learning-using-Decision-Trees-for-Occupancy-estimation-with-Imbalanced-Dataset

  Transfer Learning using Decision Trees for Occupancy estimation with Imbalanced Dataset

  Language:Jupyter Notebook310

• XH1011/HShen-FMADGL

  Language:Python3100