2017wxyzwxyz

100-plus-Python-programming-exercises-extended

100+ python programming exercise problem discussed ,explained and solved in different ways

2019-CCF-BDCI-Car_sales

2019年CCF大数据与计算智能大赛乘用车细分市场销量预测冠军解决方案

2Dconv_pub

Predicting time series with a 2D convolution network

42-workshop

Workshop material for 42 PyCharm Tips and Tricks

arxiv-sanity-preserver

Web interface for browsing, search and filtering recent arxiv submissions

Data-Science-Notes

数据科学的笔记以及资料搜集

Dynamic-Decomposition-Reconstruction-Ensemble-model

PythonForDataAnalysis

利用Python进行数据分析学习笔记以及自己寻找数据集做的练习

solver

Time-Series-Library

A Library for Advanced Deep Time Series Models.

2017wxyzwxyz/Dynamic-Decomposition-Reconstruction-Ensemble-model

2017wxyzwxyz/Time-Series-Library

A Library for Advanced Deep Time Series Models.

2017wxyzwxyz/AI_Tutorial

精选机器学习，NLP，图像识别， 深度学习等人工智能领域学习资料，搜索，推荐，广告系统架构及算法技术资料整理。算法大牛笔记汇总

2017wxyzwxyz/Autoformer

About Code release for "Autoformer: Decomposition Transformers with Auto-Correlation for Long-Term Series Forecasting" (NeurIPS 2021), https://arxiv.org/abs/2106.13008

2017wxyzwxyz/awesome-kan

A comprehensive collection of KAN(Kolmogorov-Arnold Network)-related resources, including libraries, projects, tutorials, papers, and more, for researchers and developers in the Kolmogorov-Arnold Network field.

2017wxyzwxyz/BayesianLSTM

Bayesian LSTM Implementation in PyTorch

2017wxyzwxyz/examples

Notebooks demonstrating example applications of the cleanlab library

2017wxyzwxyz/gluon-ts

Probabilistic time series modeling in Python

2017wxyzwxyz/Grokking-Deep-Learning

this repository accompanies the book "Grokking Deep Learning"

2017wxyzwxyz/ILearnDeepLearning.py

This repository contains small projects related to Neural Networks and Deep Learning in general. Subjects are closely linekd with articles I publish on Medium. I encourage you both to read as well as to check how the code works in the action.

2017wxyzwxyz/kan-polar

Kolmogorov-Arnold Networks in MATLAB

2017wxyzwxyz/Koopa

Code release for "Koopa: Learning Non-stationary Time Series Dynamics with Koopman Predictors" (NeurIPS 2023), https://arxiv.org/abs/2305.18803

2017wxyzwxyz/lag-llama

Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting

2017wxyzwxyz/liquid_time_constant_networks

Code Repository for Liquid Time-Constant Networks (LTCs)

2017wxyzwxyz/LLMs4TS

2017wxyzwxyz/mamba

2017wxyzwxyz/paper-reading

深度学习经典、新论文逐段精读

2017wxyzwxyz/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

2017wxyzwxyz/pykan

Kolmogorov Arnold Networks

2017wxyzwxyz/QSQF

Code for "Nonparametric Probabilistic Forecasting for Wind Power Generation using Quadratic Spline Quantile Function and Autoregressive Recurrent Neural Network"

2017wxyzwxyz/Quantile_reg

Adaptive algorithm for quantile regression

2017wxyzwxyz/sarimax-models

Estimate S-ARIMA-X models with Stochastic Gradient Descent or Kalman Filter

2017wxyzwxyz/simba

Simba

2017wxyzwxyz/simdkalman

Python Kalman filters vectorized as Single Instruction, Multiple Data

2017wxyzwxyz/spacetime

Code for SpaceTime 🌌⏱️. Proposed in Effectively Modeling Time Series with Simple Discrete State Spaces, ICLR 2023.

2017wxyzwxyz/SSSD

Repository for the paper: 'Diffusion-based Time Series Imputation and Forecasting with Structured State Space Models'

2017wxyzwxyz/statsmodels

Statsmodels: statistical modeling and econometrics in Python

2017wxyzwxyz/super-ai-symbol

2017wxyzwxyz/TSFpaper

This repository contains a reading list of papers on Time Series Forecasting/Prediction (TSF) and Spatio-Temporal Forecasting/Prediction (STF). These papers are mainly categorized according to the type of model.

2017wxyzwxyz/windpowerforecastDTU

Repository containing the group project Wind Power Forecasting for DTU's 02456 Deep Learning.