kailu22's Stars
ibm-granite/granite-tsfm
Foundation Models for Time Series
hughxx/tsf-new-paper-taste
A code implementation of new papers in the time series forecasting field.
stefan-jansen/machine-learning-for-trading
Code for Machine Learning for Algorithmic Trading, 2nd edition.
Zeying-Gong/PatchMixer
About Code release for "PatchMixer: A Patch-Mixing Architecture for Long-Term Time Series Forecasting"
philipperemy/n-beats
Keras/Pytorch implementation of N-BEATS: Neural basis expansion analysis for interpretable time series forecasting.
greygrease/Project-Bitcoin-Price-Predictor-NBeats--Conv1D
jdumali/wesm-nbeats
PH Energy Market Price Predictions using NBEATS and NHITS
cchallu/n-hits
cchallu/nbeatsx
Nixtla/mlforecast
Scalable machine 🤖 learning for time series forecasting.
antoinecarme/pyaf
PyAF is an Open Source Python library for Automatic Time Series Forecasting built on top of popular pydata modules.
JoaquinAmatRodrigo/skforecast
Time series forecasting with machine learning models
timeseriesAI/tsai
Time series Timeseries Deep Learning Machine Learning Python Pytorch fastai | State-of-the-art Deep Learning library for Time Series and Sequences in Pytorch / fastai
zhouhaoyi/Informer2020
The GitHub repository for the paper "Informer" accepted by AAAI 2021.
myomyint-maung/patchtst
neelblabla/transformers_for_time_series_forecasting
Inferencing 'PatchTST' and 'Informer' to harness the power of transformers for multivariate 'long sequence time-series forecasting' (LSTF).
ageron/handson-ml2
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
Mark-THU/load-analysis
A website for electical load analysis
trishitanmay1705/Electricity-Price-Forecasting-with-Deep-Neural-Networks
Tagbo-Aroh/Time-Series-Forecast-for-Electricity-LMPs
In colloboration with Southern Power Company, I completed a data science capstone project that focused on constructing a time series forecast for Locational Marginal Prices (LMPs) within the day-ahead and week-ahead energy market.
lucidrains/iTransformer
Unofficial implementation of iTransformer - SOTA Time Series Forecasting using Attention networks, out of Tsinghua / Ant group
cure-lab/LTSF-Linear
[AAAI-23 Oral] Official implementation of the paper "Are Transformers Effective for Time Series Forecasting?"
Thinklab-SJTU/Crossformer
Official implementation of our ICLR 2023 paper "Crossformer: Transformer Utilizing Cross-Dimension Dependency for Multivariate Time Series Forecasting"
yuqinie98/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
Zzz212zzZ/china-software-cup
🌪️Aeolus WindTech: A China Software Cup Innovation - This state-of-the-art wind power prediction system, developed by the Invincible Fried Chicken Team, leverages advanced machine learning to redefine accuracy in wind energy forecasting.
awslabs/gluonts
Probabilistic time series modeling in Python
thuml/Autoformer
About Code release for "Autoformer: Decomposition Transformers with Auto-Correlation for Long-Term Series Forecasting" (NeurIPS 2021), https://arxiv.org/abs/2106.13008
ourownstory/neural_prophet
NeuralProphet: A simple forecasting package
thuml/iTransformer
Official implementation for "iTransformer: Inverted Transformers Are Effective for Time Series Forecasting" (ICLR 2024 Spotlight), https://openreview.net/forum?id=JePfAI8fah
thuml/Time-Series-Library
A Library for Advanced Deep Time Series Models.