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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/littletigerhao/mt-gprmachine

공식 코드

Time Series Prediction by Multi-task GPR with Spatiotemporal Information Transformation

https://github.com/liuboxun/LLM4CP

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LLM4CP: Adapting Large Language Models for Channel Prediction

https://github.com/liudan193/Feedbacker

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From Rankings to Insights: Evaluation Should Shift Focus from Leaderboard to Feedback

https://github.com/liuxu77/unitime

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UniTime: A Language-Empowered Unified Model for Cross-Domain Time Series Forecasting

https://github.com/liuyuaa/SurvUnc

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SurvUnc: A Meta-Model Based Uncertainty Quantification Framework for Survival Analysis

https://github.com/liuzh-19/esg

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Learning the Evolutionary and Multi-scale Graph Structure for Multivariate Time Series Forecasting

https://github.com/liwk16/StackVAE

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StackVAE-G: An efficient and interpretable model for time series anomaly detection

https://github.com/lixixibj/deepvarwt-data-code

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DeepVARwT: Deep Learning for a VAR Model with Trend

https://github.com/lixixibj/forecasting-with-time-series-imaging

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Forecasting with time series imaging

https://github.com/liyaguang/DCRNN

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Diffusion Convolutional Recurrent Neural Network: Data-Driven Traffic Forecasting

https://github.com/liyouru0228/hgv

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HGV4Risk: Hierarchical Global View-guided Sequence Representation Learning for Risk Prediction

https://github.com/liyucheng09/llm-compressive

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Evaluating Large Language Models for Generalization and Robustness via Data Compression

https://github.com/ljc-fvnr/arma-attention

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Autoregressive Moving-average Attention Mechanism for Time Series Forecasting

https://github.com/ljc-fvnr/structural-aligned-mixture-of-var

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Linear Transformers as VAR Models: Aligning Autoregressive Attention Mechanisms with Autoregressive Forecasting

https://github.com/ljj-cyber/topogdn

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Multivariate Time-Series Anomaly Detection based on Enhancing Graph Attention Networks with Topological Analysis

https://github.com/lliang97/spacecraft-anonamly-detection

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Spacecraft Anomaly Detection with Attention Temporal Convolution Network

https://github.com/lll6gg/ui-r1

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UI-R1: Enhancing Efficient Action Prediction of GUI Agents by Reinforcement Learning

https://github.com/lluism/counterfacts

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Probing the Robustness of Time-series Forecasting Models with CounterfacTS

https://github.com/lmh9507/casa

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CASA: CNN Autoencoder-based Score Attention for Efficient Multivariate Long-term Time-series Forecasting

https://github.com/lnferreira/ts2net

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From Time Series to Networks in R with the ts2net Package

https://github.com/lnthach/Mr-SEQL

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Interpretable Time Series Classification using All-Subsequence Learning and Symbolic Representations in Time and Frequency Domains

https://github.com/loadingbyte/timexplain

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timeXplain -- A Framework for Explaining the Predictions of Time Series Classifiers

https://github.com/locuslab/TCN

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

https://github.com/loeweX/AmortizedCausalDiscovery

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Amortized Causal Discovery: Learning to Infer Causal Graphs from Time-Series Data

https://github.com/lostwolves/bedi

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BEDI: A Comprehensive Benchmark for Evaluating Embodied Agents on UAVs

https://github.com/louisyulu/veob-and-st

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Fast Machine Learning Method with Vector Embedding on Orthonormal Basis and Spectral Transform

https://github.com/lpphd/CHARLEE

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Multivariate Time Series Early Classification Across Channel and Time Dimensions

https://github.com/lpphd/lightwaves

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Taking ROCKET on an Efficiency Mission: Multivariate Time Series Classification with LightWaveS

https://github.com/lpphd/mtsscaling

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An Empirical Evaluation of Multivariate Time Series Classification with Input Transformation across Different Dimensions

https://github.com/lqzxt/time-r1

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Time Series Forecasting as Reasoning: A Slow-Thinking Approach with Reinforced LLMs

https://github.com/lrq577/faith

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FAITH: Frequency-domain Attention In Two Horizons for Time Series Forecasting

https://github.com/lrsoenksen/haim

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Integrated multimodal artificial intelligence framework for healthcare applications

https://github.com/lss-1138/SegRNN

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SegRNN: Segment Recurrent Neural Network for Long-Term Time Series Forecasting

https://github.com/lss-1138/SparseTSF

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SparseTSF: Modeling Long-term Time Series Forecasting with 1k Parameters

https://github.com/lsx-uniwue/susl4ts

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Semi-unsupervised Learning for Time Series Classification

https://github.com/ltorgo/performanceEstimation

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An Infra-Structure for Performance Estimation and Experimental Comparison of Predictive Models in R

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