mitchell-xiyunfeng Goto Github PK

followers: 14.0 following: 150.0 repos: 68.0 gists: 0.0

Name: Zeng haolong

Type: User

Bio: Unity of knowledge and action

Zeng haolong's Projects

loglizer

A log analysis toolkit for automated anomaly detection [ISSRE'16]

machine-learning-learning-notes

周志华《机器学习》又称西瓜书是一本较为全面的书籍，书中详细介绍了机器学习领域不同类型的算法(例如：监督学习、无监督学习、半监督学习、强化学习、集成降维、特征选择等)，记录了本人在学习过程中的理解思路与扩展知识点，希望对新人阅读西瓜书有所帮助！

materials

Bonus materials, exercises, and example projects for our Python tutorials

美国大学生数学建模竞赛、全国大学生数学建模竞赛、华为杯研究生数学建模、数学建模美赛论文，数学建模国赛论文、LaTeX模板、国赛LaTeX模板、美赛LaTeX模板、mathorcup历年论文、研究生数学建模历年论文、电工杯、华中赛、APMCM亚太地区数学建模、深圳杯、中青杯、华东杯、数维杯、东三省数学建模、认证杯、数学建模书籍、数学建模算法、国赛评阅要点、数学建模word模板、软件模型算法汇总、MATLAB算法、常用Matlab代码、智能算法、现代的算法、图论算法、优化算法

mchmm

Markov Chains and Hidden Markov Models in Python

mcm-2022

2022年美赛C题交易策略

mercbo

Python implementation of Mercer Features for Efficient Combinatorial Bayesian Optimization

mydocsify

nbpreview

Render Jupyter/IPython notebooks without running a notebook server.

paddlespatial

PaddleSpatial is an open-source spatial-temporal computing tool based on PaddlePaddle.

patchtst

An offical implementation of PatchTST: "A Time Series is Worth 64 Words: Long-term Forecasting with Transformers." (ICLR 2023) https://arxiv.org/abs/2211.14730

piml-toolbox

PiML (Python Interpretable Machine Learning) toolbox for model development and model validation

poisson_flow

Code for NeurIPS 2022 Paper, "Poisson Flow Generative Models"

pot

POT : Python Optimal Transport

prompt-patterns

Prompt 编写模式：如何将思维框架赋予机器，以设计模式的形式来思考 prompt

pycaret

An open-source, low-code machine learning library in Python

pyrcca

Regularized kernel canonical correlation analysis in Python

python

All Algorithms implemented in Python

python-louvain

Louvain Community Detection

pytorch-ts

PyTorch based Probabilistic Time Series forecasting framework based on GluonTS backend

pytorch_geometric_temporal

PyTorch Geometric Temporal: Spatiotemporal Signal Processing with Neural Machine Learning Models (CIKM 2021)

researchhowto

Slides about how to do research

sagemaker-deep-demand-forecast

Using Deep Learning for Demand Forecasting with Amazon SageMaker

sui-airesearch

该资源将应用人工智能技术研究水族文化、文字和古籍。为更好的抢救和保护濒危水族文字和非物质文化遗产，作者申请并开源了该项目，主要通过人工智能技术识别水书，构建与汉字的自动翻译系统，实现水族本体和文献知识图谱构建，挖掘新词并溯源民族变迁历史。作者回到家乡贵州教书以来，对利用AI抢救民族文物研究产生浓厚兴趣并后半生都将致力于该研究中，包括侗族大歌、苗族飞歌语音识别研究，王阳明文化研究，少数民族古籍文字保护及文化图腾识别都会陆续展开，希望有共同爱好的朋友参与进来，一起加油。

taddy_pytorch

A Pytorch implement of paper "Anomaly detection in dynamic graphs via transformer" (TADDY).

tiara

Implementation of Time-aware Random Walk Diffusion to Improve Dynamic Graph Learning (AAAI-23)

timeseries

Implementation of deep learning models for time series in PyTorch.

torchcde

Differentiable controlled differential equation solvers for PyTorch with GPU support and memory-efficient adjoint backpropagation.

mitchell-xiyunfeng Goto Github PK

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