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Time Series Analysis

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.

( Image credit: Autoregressive CNNs for Asynchronous Time Series )

Papers

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Showing 901–925 of 6748 papers

TitleStatusHype
Imaging Time-Series to Improve Classification and ImputationCode1
Variational Recurrent Auto-EncodersCode1
Highly comparative time-series analysis: The empirical structure of time series and their methodsCode1
Emergence of Functionally Differentiated Structures via Mutual Information Optimization in Recurrent Neural NetworksCode0
Process mining-driven modeling and simulation to enhance fault diagnosis in cyber-physical systems—0
A Review of the Long Horizon Forecasting Problem in Time Series AnalysisCode0
Time-IMM: A Dataset and Benchmark for Irregular Multimodal Multivariate Time Series—0
The interplay of robustness and generalization in quantum machine learningCode0
Trojan Horse Hunt in Time Series Forecasting for Space Operations—0
Bridging Subjective and Objective QoE: Operator-Level Aggregation Using LLM-Based Comment Analysis and Network MOS Comparison—0
Cluster-Aware Causal Mixer for Online Anomaly Detection in Multivariate Time Series—0
Exposing the Impact of GenAI for Cybercrime: An Investigation into the Dark Side—0
From Images to Signals: Are Large Vision Models Useful for Time Series Analysis?—0
Intraday Functional PCA Forecasting of Cryptocurrency Returns—0
VISTA: Vision-Language Inference for Training-Free Stock Time-Series Analysis—0
LASSO-ODE: A framework for mechanistic model identifiability and selection in disease transmission modelingCode0
Large Language models for Time Series Analysis: Techniques, Applications, and Challenges—0
Byte Pair Encoding for Efficient Time Series Forecasting—0
Level Generation with Quantum Reservoir Computing—0
TSPulse: Dual Space Tiny Pre-Trained Models for Rapid Time-Series Analysis—0
MONAQ: Multi-Objective Neural Architecture Querying for Time-Series Analysis on Resource-Constrained DevicesCode0
The Impact of COVID-19 on FinTech Lending in Indonesia: Evidence From Interrupted Time Series Analysis—0
Recognizing Ornaments in Vocal Indian Art Music with Active Annotation—0
Dual-Forecaster: A Multimodal Time Series Model Integrating Descriptive and Predictive Texts—0
Geospatial and Temporal Trends in Urban Transportation: A Study of NYC Taxis and Pathao Food Deliveries—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1naive classifierF187.47—Unverified
2GRU-D - APC (n = 1)F127.3—Unverified
3GRU-APC (n = 1)F125.7—Unverified
4GRU-DF122.5—Unverified
5GRUF122.3—Unverified
6GRU-SimpleF122.2—Unverified
7GRU-MeanF122.1—Unverified
#ModelMetricClaimedVerifiedStatus
1SepTr% Test Accuracy98.51—Unverified
2ViT% Test Accuracy98.11—Unverified
3FlexTCN-4% Test Accuracy97.73—Unverified
4MatchboxNet% Test Accuracy97.4—Unverified
5CKCNN (100k)% Test Accuracy95.27—Unverified
6FlexTCN-6% Test Accuracy (Raw Data)91.73—Unverified
#ModelMetricClaimedVerifiedStatus
1ResBiLSTMMAE0.13—Unverified