Yan9564

Yan9564's Stars

• mims-harvard/nimfa

  Nimfa: Nonnegative matrix factorization in Python

  Language:Python543135

• shinke-li/Primtive3D

  Dataset Generation Code for CVPR 2022 Paper Primtive3D: 3D Object Dataset Synthesis from Randomly Assembled Primitives

  Language:Python10

• dakuang/symnmf

  Symmetric NMF for graph clustering

  Language:Matlab2810

• danieltan07/dagmm

  My attempt at reproducing the paper Deep Autoencoding Gaussian Mixture Model for Unsupervised Anomaly Detection

  Language:Jupyter Notebook398106

• JmlrOrg/v22

  Volume 22 of JMLR

  2

• manfred-jaeger-aalborg/aim_for_gauss

  Python implementation of AIM for binned or incomplete Gaussians

  Language:Python1

• oval-group/borat

  A Stochastic Bundle Method for Interpolating Networks. JMLR 2021.

  Language:Python32

• SetarehAr/ADMMBO

  An implementation of "ADMMBO, An ADMM Framework for Bayesian Optimization with Unknown Constraints''

  Language:MATLAB208

• mlpotter/Transformer_Time_Series

  Enhancing the Locality and Breaking the Memory Bottleneck of Transformer on Time Series Forecasting (NeurIPS 2019)

  Language:Jupyter Notebook547100

• philipperemy/keras-attention

  Keras Attention Layer (Luong and Bahdanau scores).

  Language:Python2.8k675

• locuslab/deq

  [NeurIPS'19] Deep Equilibrium Models

  Language:Python72779

• amitesh863/nbeats_forecast

  N-Beats library implementation

  Language:Python8618

• Mamba413/cope

  Off-Policy Interval Estimation withConfounded Markov Decision Process

  Language:Python53

• dnncode/LTPP-Data

  Processed Long-Term Pavement Performance (LTPP) data

  51

• msk-apps/msk-markdown

  MSK Markdown is light markdown editor and viewer.

  Language:JavaScript16238

• Spratm-Asleaf/DRSE-PhD-Thesis

  Online supplementary materials of my PhD thesis titled "Distributionally Robust State Estimation"

  21

• sunface/rust-course

  “连续八年成为全世界最受喜爱的语言，无 GC 也无需手动内存管理、极高的性能和安全性、过程/OO/函数式编程、优秀的包管理、JS 未来基石" — 工作之余的第二语言来试试 Rust 吧。本书拥有全面且深入的讲解、生动贴切的示例、德芙般丝滑的内容，这可能是目前最用心的 Rust 中文学习教程 / Book

  Language:Rust25.8k2.2k

• ZhaoZhibin/UDTL

  Source codes for the paper "Applications of Unsupervised Deep Transfer Learning to Intelligent Fault Diagnosis: A Survey and Comparative Study" published in TIM

  Language:Python421106

• thuml/Transfer-Learning-Library

  Transfer Learning Library for Domain Adaptation, Task Adaptation, and Domain Generalization

  Language:Python3.4k558

• hehonghui/the-economist-ebooks

  经济学人(含音频)、纽约客、自然、新科学人、卫报、科学美国人、连线、大西洋月刊、国家地理等英语杂志免费下载,支持epub、mobi、pdf格式, 每周更新.

  Language:CSS9.9k

• dnncode/Boost-R

  Boost-R: Boosting for recurrence data

  Language:R2

• jiaxiang-cheng/PyTorch-Transformer-for-RUL-Prediction

  Transformer implementation with PyTorch for remaining useful life prediction on turbofan engine with NASA CMAPSS data set. Inspired by Mo, Y., Wu, Q., Li, X., & Huang, B. (2021). Remaining useful life estimation via transformer encoder enhanced by a gated convolutional unit. Journal of Intelligent Manufacturing, 1-10.

  Language:Python23048

• songyer/Fault_Diagnosis

  基于深度学习的滚动轴承故障诊断方法

  Language:Python17031

• shenweichen/GraphNeuralNetwork

  Implementation and experiments of graph neural netwokrs, like gcn,graphsage,gat,etc.

  Language:Python788182

• liguge/Fault-diagnosis-for-small-samples-based-on-attention-mechanism

  基于注意力机制的少量样本故障诊断 pytorch

  Language:Python20012

• PacktPublishing/The-Kaggle-Book

  Code Repository for The Kaggle Book, Published by Packt Publishing

  Language:Jupyter Notebook2.2k455

• dair-ai/ml-visuals

  🎨 ML Visuals contains figures and templates which you can reuse and customize to improve your scientific writing.

  13.6k1.4k

• getgridea/gridea

  ✍️ A static blog writing client (一个静态博客写作客户端)

  Language:TypeScript10k799

• daiquocnguyen/Graph-Transformer

  Universal Graph Transformer Self-Attention Networks (TheWebConf WWW 2022) (Pytorch and Tensorflow)

  Language:Python65379

• balcilar/Spectral-Designed-Graph-Convolutions

  Codes for "Bridging the Gap Between Spectral and Spatial Domains in Graph Neural Networks" paper

  Language:Python496