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Time Series Forecasting

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하위 태스크: 6
평가표: 86
보존된 평가 기록: 538

Time Series Forecasting is the task of fitting a model to historical, time-stamped data in order to predict future values. Traditional approaches include moving average, exponential smoothing, and ARIMA, though models as various as RNNs, Transformers, or XGBoost can also be applied. The most popular benchmark is the ETTh1 dataset. Models are typically evaluated using the Mean Square Error (MSE) or Root Mean Square Error (RMSE).

<span style="color:grey; opacity: 0.6">( Image credit: ThaiBinh Nguyen )</span>

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/iDEA-iSAIL-Lab-UIUC/TaTS

공식 코드

Language in the Flow of Time: Time-Series-Paired Texts Weaved into a Unified Temporal Narrative

https://github.com/ibm-granite/granite-tsfm

공식 코드

Tiny Time Mixers (TTMs): Fast Pre-trained Models for Enhanced Zero/Few-Shot Forecasting of Multivariate Time Series

https://github.com/ibm/multi-variate-parallel-transformer

공식 코드

A foundation model with multi-variate parallel attention to generate neuronal activity

https://github.com/ibm/spatial-lstm

공식 코드

A spatio-temporal LSTM model to forecast across multiple temporal and spatial scales

https://github.com/ibm/tsfm

공식 코드

TSMixer: Lightweight MLP-Mixer Model for Multivariate Time Series Forecasting

https://github.com/icantnamemyself/gpht

공식 코드

Generative Pretrained Hierarchical Transformer for Time Series Forecasting

https://github.com/ikeyang/machine-vision-assisted-deep-time-series-analysis-mv-dtsa-

공식 코드

Your time series is worth a binary image: machine vision assisted deep framework for time series forecasting

https://github.com/ikeyang/vitime

공식 코드

ViTime: A Visual Intelligence-Based Foundation Model for Time Series Forecasting

https://github.com/indrajeet3333/covid-19-forecasting

공식 코드

Improving Neural Networks for Time Series Forecasting using Data Augmentation and AutoML

https://github.com/ivan-chai/hotpp-benchmark

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HoTPP Benchmark: Are We Good at the Long Horizon Events Forecasting?

https://github.com/jackyue1994/FreEformer

공식 코드

FreEformer: Frequency Enhanced Transformer for Multivariate Time Series Forecasting

https://github.com/jackyue1994/OLinear

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OLinear: A Linear Model for Time Series Forecasting in Orthogonally Transformed Domain

https://github.com/jafarbakhshaliyev/wave-augs

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Wave-Mask/Mix: Exploring Wavelet-Based Augmentations for Time Series Forecasting

https://github.com/jain15mayank/PWV-Forecasts-Using-LSTM

공식 코드

Forecasting Precipitable Water Vapor Using LSTMs

https://github.com/jcastro295/gegengnn

공식 코드

Gegenbauer Graph Neural Networks for Time-varying Signal Reconstruction

https://github.com/jeongwhanchoi/STG-NCDE

공식 코드

Graph Neural Controlled Differential Equations for Traffic Forecasting

https://github.com/jeremy-qin/timeview

공식 코드

Robust Multi-Modal Forecasting: Integrating Static and Dynamic Features

https://github.com/jimengshi/pararcnn-time-series-forecasting

공식 코드

Explainable Parallel RCNN with Novel Feature Representation for Time Series Forecasting

https://github.com/jimengshi/refine

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ReFine: Boosting Time Series Prediction of Extreme Events by Reweighting and Fine-tuning

https://github.com/jingge326/flextsf

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FlexTSF: A Universal Forecasting Model for Time Series with Variable Regularities

https://github.com/jingjing-unilu/HPO_transformer_time_series

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A Unified Hyperparameter Optimization Pipeline for Transformer-Based Time Series Forecasting Models

https://github.com/jingjing-unilu/pca_transformer

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Transformer Multivariate Forecasting: Less is More?

https://github.com/jingminsun/prose_v1

공식 코드

Time-Series Forecasting, Knowledge Distillation, and Refinement within a Multimodal PDE Foundation Model

https://github.com/jingzheshi/scalinglawfortimeseriesforecasting

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Scaling Law for Time Series Forecasting

https://github.com/jjdabr/forecastNet

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ForecastNet: A Time-Variant Deep Feed-Forward Neural Network Architecture for Multi-Step-Ahead Time-Series Forecasting

https://github.com/jjgarau/gnnd

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Integrating LSTMs and GNNs for COVID-19 Forecasting

https://github.com/jl-tong/pdtrans

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Probabilistic Decomposition Transformer for Time Series Forecasting

https://github.com/jmleites/Lag_selection

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Lag Selection for Univariate Time Series Forecasting using Deep Learning: An Empirical Study

https://github.com/joeland4/fsatten-soatten

공식 코드

Revisiting Attention for Multivariate Time Series Forecasting

https://github.com/jsun57/stmae

공식 코드

Revealing the Power of Masked Autoencoders in Traffic Forecasting

https://github.com/junwoopark92/ECMLPKDD2023-ReLD

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Deep Imbalanced Time-series Forecasting via Local Discrepancy Density

https://github.com/junwoopark92/revisiting-llms-zeroshot-forecaster

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Revisiting LLMs as Zero-Shot Time-Series Forecasters: Small Noise Can Break Large Models

https://github.com/junwoopark92/self-supervised-contrastive-forecsating

공식 코드

Self-Supervised Contrastive Learning for Long-term Forecasting

https://github.com/kaist-dmlab/VarDrop

공식 코드

VarDrop: Enhancing Training Efficiency by Reducing Variate Redundancy in Periodic Time Series Forecasting

https://github.com/kamarain/minimal_time_series_transformer

공식 코드

Minimal Time Series Transformer

https://github.com/kaushik-rohit/timeseries-prediction

공식 코드

Performance evaluation of deep neural networks for forecasting time-series with multiple structural breaks and high volatility

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