yunpingwang27

yunpingwang27's Stars

• Blealtan/efficient-kan

  An efficient pure-PyTorch implementation of Kolmogorov-Arnold Network (KAN).

  Language:Python4.1k3640361

• geph-official/geph4-client

  Geph (迷霧通) is a modular Internet censorship circumvention system designed specifically to deal with national filtering.

  Language:Rust2.9k39178342

• JuliaPy/PythonCall.jl

  Python and Julia in harmony.

  Language:Julia826843966

• iMoonLab/DeepHypergraph

  A pytorch library for graph and hypergraph computation.

  Language:Python674104864

• scikit-tda/scikit-tda

  Topological Data Analysis for Python🐍

  Language:Python527182255

• cvignac/DiGress

  code for the paper "DiGress: Discrete Denoising diffusion for graph generation"

  Language:Python369710176

• gwastro/pycbc

  Core package to analyze gravitational-wave data, find signals, and study their parameters. This package was used in the first direct detection of gravitational waves (GW150914), and is used in the ongoing analysis of LIGO/Virgo data.

  Language:Python31742847354

• Ripser/ripser

  Ripser: efficient computation of Vietoris–Rips persistence barcodes

  Language:C++315253578

• jichangzhu/JichangTuijian

  2024最新好用的机场推荐与节点分享

  171209

• BorgwardtLab/topological-autoencoders

  Code for the paper "Topological Autoencoders" by Michael Moor, Max Horn, Bastian Rieck, and Karsten Borgwardt.

  Language:Python1417533

• ermongroup/GraphScoreMatching

  Official implementation for the paper: Permutation Invariant Graph Generation via Score-Based Generative Modeling

  Language:Python10611419

• giotto-ai/giotto-deep

  Deep learning made topological.

  Language:Python8065311

• caokai1073/uniPort

  a unified single-cell data integration framework by optimal transport

  Language:Python31393

• Hongjie97/GraphTransformer_BrainAge

  Language:Python21111

• gwosc-tutorial/LOSC_Event_tutorial

  Tutorial for working with binary black hole data. http://mybinder.org/repo/losc-tutorial/LOSC_Event_tutorial

  Language:Jupyter Notebook208121

• NineAbyss/ZeroG

  The official implement of SIGKDD'24 paper: ZeroG: Investigating Cross-dataset Zero-shot Transferability in Graphs

  Language:Python20123

• salvaba94/G2Net

  Find gravitational wave signals from binary black hole collisions.

  Language:Python15112

• gwosc-tutorial/quickview

  Make summary plots for any short segment of LIGO data. http://mybinder.org/repo/losc-tutorial/quickview

  Language:Jupyter Notebook143111

• cw-seo/SiReN-reco

  Language:Python94

• geonwooko/DINES

  About Implementation of Learning Disentangled Representations in Signed Directed Graphs without Social Assumptions (InfoSci-24)

  Language:Python9103

• caixunshiren/GCNGDE_Simulation_for_EEG_analysis

  Analyzing EEG dataset using graph convolutional neural network and graph differential equations.

  Language:Jupyter Notebook8211

• ExpectationMax/torch_persistent_homology

  Language:C++7442

• AI-HPC-Research-Team/Space_signal_detection_all4

  Gravitational wave data denoising and signal detection for space-based detections

  Language:Python5224

• jaketae/graph-neural-ode

  Graph neural ordinary differential equations

  Language:Python520

• fabiocarrara/gw-glitches

  Gravitational Waves Noise Glitches Classification using Deep Learning

  Language:Python410

• yunpingwang27/weibo-spider-LDA

  瑞幸联名：爬虫+LDA主题分析

  Language:Python3000

• rishabkr/Linear-Algebra-and-Sparse-Matrix-Algorithms

  Implementation of Sparse Matrix algorithms and Linear Algebra techniques (eg. Faster LU decomposition)

  Language:Jupyter Notebook2200

• KYangZ/parallel-gpu-matrix-computations

  Parallel GPU based algorithms to solve linear systems, invert matrices, compute determinants, and LU factorizations.

  Language:Cuda1

• lucasmoschen/topological-data-analysis

  Homework and codes in the Topological Data Analysis with Persistent Homology course at FGV EMAp.

  Language:Jupyter Notebook120

• zhouzhouce/Parallel--LU-decomposition

  A parallel distributed algorithm implementation to solve linear system problems, which applied high-performance computational mathematics methodologies using MPI in Intel DevCloud JupyterLab & Python

  Language:Python110