SOTAVerified

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 2951–3000 of 6748 papers

TitleStatusHype
Functional Classwise Principal Component Analysis: A Novel Classification Framework—0
Functional Bayesian Filter—0
Functional Annotation of Human Cognitive States using Graph Convolution Networks—0
Conditional independence testing with a single realization of a multivariate nonstationary nonlinear time series—0
Granger Mediation Analysis of Multiple Time Series with an Application to fMRI—0
Graph2Seq: Scalable Learning Dynamics for Graphs—0
A Robust Score-Driven Filter for Multivariate Time Series—0
Graph Attention Recurrent Neural Networks for Correlated Time Series Forecasting -- Full version—0
A Modified Dynamic Time Warping (MDTW) Approach and Innovative Average Non-Self Match Distance (ANSD) Method for Anomaly Detection in ECG Recordings—0
Fully Learnable Deep Wavelet Transform for Unsupervised Monitoring of High-Frequency Time Series—0
Conditional heteroskedasticity in crypto-asset returns—0
Fully convolutional networks for structural health monitoring through multivariate time series classification—0
Conditional Generative Models for Counterfactual Explanations—0
Graph-based Predictable Feature Analysis—0
Graph-based Reinforcement Learning for Active Learning in Real Time: An Application in Modeling River Networks—0
Graph Anomaly Detection in Time Series: A Survey—0
A Robust Data-driven Process Modeling Applied to Time-series Stochastic Power Flow—0
Frugal day-ahead forecasting of multiple local electricity loads by aggregating adaptive models—0
From time-series transcriptomics to gene regulatory networks: a review on inference methods—0
Conditional Generative Adversarial Networks to Model Urban Outdoor Air Pollution—0
A Robust and Explainable Data-Driven Anomaly Detection Approach For Power Electronics—0
Graph Hierarchical Convolutional Recurrent Neural Network (GHCRNN) for Vehicle Condition Prediction—0
Graphical estimation of multivariate count time series—0
Graphical LASSO Based Model Selection for Time Series—0
From Time Series to Euclidean Spaces: On Spatial Transformations for Temporal Clustering—0
Graphical RNN Models—0
From Text to Trends: A Unique Garden Analytics Perspective on the Future of Modern Agriculture—0
Graph Learning from Multivariate Dependent Time Series via a Multi-Attribute Formulation—0
Graph Message Passing with Cross-location Attentions for Long-term ILI Prediction—0
Graph Neural Alchemist: An innovative fully modular architecture for time series-to-graph classification—0
From Static to Dynamic Node Embeddings—0
Graph neural network-based fault diagnosis: a review—0
From sleep medicine to medicine during sleep: A clinical perspective—0
GRAPHSHAP: Explaining Identity-Aware Graph Classifiers Through the Language of Motifs—0
A Robust and Efficient Multi-Scale Seasonal-Trend Decomposition—0
Graph Spectral Embedding for Parsimonious Transmission of Multivariate Time Series—0
From Rules to Regs: A Structural Topic Model of Collusion Research—0
Grasping Core Rules of Time Series through Pure Models—0
GraSSNet: Graph Soft Sensing Neural Networks—0
From learning gait signatures of many individuals to reconstructing gait dynamics of one single individual—0
From Known to Unknown: Knowledge-guided Transformer for Time-Series Sales Forecasting in Alibaba—0
Concept-drifting Data Streams are Time Series; The Case for Continuous Adaptation—0
Grey Models for Short-Term Queue Length Predictions for Adaptive Traffic Signal Control—0
Griffon: Reasoning about Job Anomalies with Unlabeled Data in Cloud-based Platforms—0
Grouped Convolutional Neural Networks for Multivariate Time Series—0
Grouped self-attention mechanism for a memory-efficient Transformer—0
ArNet-ECG: Deep Learning for the Detection of Atrial Fibrillation from the Raw Electrocardiogram—0
GrowliFlower: An image time series dataset for GROWth analysis of cauLIFLOWER—0
A Model Combining Convolutional Neural Network and LightGBM Algorithm for Ultra-Short-Term Wind Power Forecasting—0
A Data-driven Market Simulator for Small Data Environments—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