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Time Series Analysis

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하위 태스크: 12
평가표: 3
보존된 평가 기록: 14

Time Series Analysis is a statistical technique used to analyze and model time-based data. It is used in various fields such as finance, economics, and engineering to analyze patterns and trends in data over time. The goal of time series analysis is to identify the underlying patterns, trends, and seasonality in the data, and to use this information to make informed predictions about future values.

<span style="color:grey; opacity: 0.6">( Image credit: Autoregressive CNNs for Asynchronous Time Series )</span>

코드

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

https://github.com/tianhai123/MIM

Memory In Memory: A Predictive Neural Network for Learning Higher-Order Non-Stationarity from Spatiotemporal Dynamics

https://github.com/tianzhou2011/FiLM

FiLM: Frequency improved Legendre Memory Model for Long-term Time Series Forecasting

https://github.com/tijsmaas/TrafficPrediction

Diffusion Convolutional Recurrent Neural Network: Data-Driven Traffic Forecasting

https://github.com/timeseriesAI/tsai

Time Series Classification from Scratch with Deep Neural Networks: A Strong Baseline

https://github.com/timeseriesAI/tsai/blob/main/tsai/models/InceptionTime.py

InceptionTime: Finding AlexNet for Time Series Classification

https://github.com/timeseriesAI/tsai/blob/main/tsai/models/MINIROCKET_Pytorch.py

MINIROCKET: A Very Fast (Almost) Deterministic Transform for Time Series Classification

https://github.com/timeseriesAI/tsai/blob/main/tsai/models/RNN_FCN.py

Multivariate LSTM-FCNs for Time Series Classification

https://github.com/timeseriesAI/tsai/blob/main/tsai/models/TST.py

A Transformer-based Framework for Multivariate Time Series Representation Learning

https://github.com/timeseriesAI/tsai/blob/main/tsai/models/XCM.py

XCM: An Explainable Convolutional Neural Network for Multivariate Time Series Classification

https://github.com/timeseriesAI/tsai/blob/main/tsai/models/XceptionTime.py

XceptionTime: A Novel Deep Architecture based on Depthwise Separable Convolutions for Hand Gesture Classification

https://github.com/timeseriesAI/tsai/blob/main/tsai/models/mWDN.py

Multilevel Wavelet Decomposition Network for Interpretable Time Series Analysis

https://github.com/timeseriesAI/tsai/tree/main/tsai/models

LSTM Fully Convolutional Networks for Time Series Classification

https://github.com/timradtke/recur

Forecasting with time series imaging

https://github.com/titu1994/Adversarial-Attacks-Time-Series

Adversarial Attacks on Time Series

https://github.com/titu1994/LSTM-FCN-Ablation

Insights into LSTM Fully Convolutional Networks for Time Series Classification

https://github.com/titu1994/MLSTM-FCN

LSTM Fully Convolutional Networks for Time Series Classification

https://github.com/titu1994/tfdiffeq

Neural Ordinary Differential Equations

https://github.com/torchspatiotemporal/tsl

Filling the G_ap_s: Multivariate Time Series Imputation by Graph Neural Networks

https://github.com/tpetaja1/tvgl

Network Inference via the Time-Varying Graphical Lasso

https://github.com/tqchen/xgboost

XGBoost: A Scalable Tree Boosting System

https://github.com/trqminh/seq2seq

Sequence to Sequence Learning with Neural Networks

https://github.com/trustagi-lab/mtgode

Multivariate Time Series Forecasting with Dynamic Graph Neural ODEs

https://github.com/tryambakganguly/Spatiotemporal-Attention-Mechanism

Spatiotemporal Attention for Multivariate Time Series Prediction and Interpretation

https://github.com/tvayer/FGW

Optimal Transport for structured data with application on graphs

https://github.com/tw-yuhsi/a-new-perspective-for-shuttlecock-hitting-event-detection

An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling

https://github.com/ucl-exoplanets/deepARTransit

DeepAR: Probabilistic Forecasting with Autoregressive Recurrent Networks

https://github.com/uctb/uctb

Diffusion Convolutional Recurrent Neural Network: Data-Driven Traffic Forecasting

https://github.com/uea-machine-learning/tsml

Scalable Dictionary Classifiers for Time Series Classification

https://github.com/ulissigroup/uncertainty_benchmarking

Accurate Uncertainties for Deep Learning Using Calibrated Regression

https://github.com/umeiko/mindspore-seq2seq

Sequence to Sequence Learning with Neural Networks

https://github.com/umngangaliqiu/dnn4gnetworking

Real-time Power System State Estimation and Forecasting via Deep Neural Networks

https://github.com/urban-resilience-lab/deepcovidnet

DeepCOVIDNet: An Interpretable Deep Learning Model for Predictive Surveillance of COVID-19 Using Heterogeneous Features and their Interactions

https://github.com/urbanarchitect/urbanarchitect

Urban Architect: Steerable 3D Urban Scene Generation with Layout Prior

https://github.com/usneek/sequence-embeddings

Activity2Vec: Learning ADL Embeddings from Sensor Data with a Sequence-to-Sequence Model

https://github.com/utanaka2000/fairseq

Diverse Beam Search: Decoding Diverse Solutions from Neural Sequence Models

https://github.com/uw-mad-dash/pgt_index

Spatial-Temporal Large Language Model for Traffic Prediction

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