Official implementation for "AutoTimes: Autoregressive Time Series Forecasters via Large Language Models"
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Updated
Jun 6, 2024 - Python
Official implementation for "AutoTimes: Autoregressive Time Series Forecasters via Large Language Models"
Extreme Gradient Boosting (XGBoost) model for predicting hourly traffic volume. Utilized MAPE for model scoring, train-test splits with TimeSeriesSplit and hyperparameter tuning with GridSearchCV.
Code developed for the authors master's thesis "Novel Deep Learning Strategies for Time Series Forecasting" during the academic year 2023/2024 at the Norwegian University of Science and Technology (NTNU).
A curated list of projects based on applications of Machine learning and Actuarial Science.
[ICLR 2024] Official implementation of "TimeMixer: Decomposable Multiscale Mixing for Time Series Forecasting"
Analise dos retornos da companhia aerea LATAM na bolsa chilena usando series temporais . Esse trabalho é o projeto final da disciplina ME607-Series Temporais na UNICAMP
Unified Training of Universal Time Series Forecasting Transformers
TimeGPT-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 🚀.
Time-Series Work Summary in CS Top Conferences (NIPS, ICML, ICLR, KDD, AAAI, WWW, IJCAI, CIKM, ICDM, ICDE, etc.)
Resources about time series forecasting and deep learning.
Time-series prediction using a multi-modal 1D Convolutional Neural Network
EzStacking: From data to Kubernetes thru Scikit-Learn, FastAPI and Docker in a few clicks and command lines!
Chronos: Pretrained (Language) Models for Probabilistic Time Series Forecasting
a collection of NLP projects&tools. 自然语言处理方向项目和工具集合。
[ICLR 2024] Official implementation of " 🦙 Time-LLM: Time Series Forecasting by Reprogramming Large Language Models"
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.
Probabilistic time series modeling in Python
To develop an advance forecasting model that adeptly incorporates solar irradiance data, leveraging its predictive capabilities to elevate forecasting performance and reliability.
Deep learning PyTorch library for time series forecasting, classification, and anomaly detection (originally for flood forecasting).
A fast, effective and accurate algorithm for univariate time series forecasting
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