2,069 skills found · Page 1 of 69
google-research / TimesfmTimesFM (Time Series Foundation Model) is a pretrained time-series foundation model developed by Google Research for time-series forecasting.
facebook / ProphetTool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
unit8co / DartsA python library for user-friendly forecasting and anomaly detection on time series.
facebookresearch / KatsKats, a kit to analyze time series data, a lightweight, easy-to-use, generalizable, and extendable framework to perform time series analysis, from understanding the key statistics and characteristics, detecting change points and anomalies, to forecasting future trends.
amazon-science / Chronos ForecastingChronos: Pretrained Models for Time Series Forecasting
awslabs / GluontsProbabilistic time series modeling in Python
sktime / Pytorch ForecastingTime series forecasting with PyTorch
Nixtla / NixtlaTimeGPT-1: production ready pre-trained Time Series Foundation Model for forecasting and anomaly detection. Generative pretrained transformer for time series trained on over 100B data points. It's capable of accurately predicting various domains such as retail, electricity, finance, and IoT with just a few lines of code 🚀.
ddz16 / TSFpaperThis 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.
qingsongedu / Time Series Transformers ReviewA professionally curated list of awesome resources (paper, code, data, etc.) on transformers in time series.
Alro10 / Deep Learning Time SeriesList of papers, code and experiments using deep learning for time series forecasting
KimMeen / Time LLM[ICLR 2024] Official implementation of " 🦙 Time-LLM: Time Series Forecasting by Reprogramming Large Language Models"
yuqinie98 / PatchTSTAn offical implementation of PatchTST: "A Time Series is Worth 64 Words: Long-term Forecasting with Transformers." (ICLR 2023) https://arxiv.org/abs/2211.14730
cure-lab / LTSF Linear[AAAI-23 Oral] Official implementation of the paper "Are Transformers Effective for Time Series Forecasting?"
curiousily / Getting Things Done With PytorchJupyter Notebook tutorials on solving real-world problems with Machine Learning & Deep Learning using PyTorch. Topics: Face detection with Detectron 2, Time Series anomaly detection with LSTM Autoencoders, Object Detection with YOLO v5, Build your first Neural Network, Time Series forecasting for Coronavirus daily cases, Sentiment Analysis with BER
AIStream-Peelout / Flow ForecastDeep learning PyTorch library for time series forecasting, classification, and anomaly detection (originally for flood forecasting).
thuml / ITransformerOfficial implementation for "iTransformer: Inverted Transformers Are Effective for Time Series Forecasting" (ICLR 2024 Spotlight)
IBM / AssetOpsBenchAssetOpsBench - Industry 4.0: A unified benchmark and framework for building, orchestrating, and evaluating domain-specific AI agents for Industry 4.0 asset operations and maintenance, with 460+ scenarios, 5 specialist agents (IoT, FMSR, TSFM, Work Order,...), and multi-agent orchestration blueprints (MetaAgent, AgentHive) over MCP.
WenjieDu / PyPOTSA Python toolkit/library for reality-centric machine/deep learning & data mining on partially-observed time series, with 50+ SOTA neural network models for scientific analysis tasks (imputation, classification, clustering, forecasting, anomaly detection, cleaning) on incomplete industrial irregularly-sampled multivariate TS with NaN missing values
kwuking / TimeMixer[ICLR 2024] Official implementation of "TimeMixer: Decomposable Multiscale Mixing for Time Series Forecasting"
