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

Showing 18511875 of 6748 papers

TitleStatusHype
Anomaly detection in the dynamics of web and social networksCode0
Domain Adaptation Under Behavioral and Temporal Shifts for Natural Time Series Mobile Activity RecognitionCode0
Don't Get Me Wrong: How to Apply Deep Visual Interpretations to Time SeriesCode0
Temporally-Reweighted Chinese Restaurant Process Mixtures for Clustering, Imputing, and Forecasting Multivariate Time SeriesCode0
Dynamic cyber risk estimation with Competitive Quantile AutoregressionCode0
Anomaly Detection in Multivariate Non-stationary Time Series for Automatic DBMS DiagnosisCode0
DLBI: Deep learning guided Bayesian inference for structure reconstruction of super-resolution fluorescence microscopyCode0
Distribution Agnostic Symbolic Representations for Time Series Dimensionality Reduction and Online Anomaly DetectionCode0
Distributional conformal predictionCode0
The Area of the Convex Hull of Sampled Curves: a Robust Functional Statistical Depth MeasureCode0
The DeepCAR Method: Forecasting Time-Series Data That Have Change PointsCode0
Deep Learning and Linear Programming for Automated Ensemble Forecasting and InterpretationCode0
A case study of spatiotemporal forecasting techniques for weather forecastingCode0
Deep reinforcement learning for time series: playing idealized trading gamesCode0
From the logistic-sigmoid to nlogistic-sigmoid: modelling the COVID-19 pandemic growthCode0
Distillation Enhanced Time Series Forecasting Network with Momentum Contrastive LearningCode0
Distributed and parallel time series feature extraction for industrial big data applicationsCode0
Does Terrorism Trigger Online Hate Speech? On the Association of Events and Time SeriesCode0
Boosting: Why You Can Use the HP FilterCode0
The UCR Time Series ArchiveCode0
Anomaly detection in dynamic networksCode0
Discovering Synchronized Subsets of Sequences: A Large Scale SolutionCode0
Automatic alignment of surgical videos using kinematic dataCode0
DisCoVQA: Temporal Distortion-Content Transformers for Video Quality AssessmentCode0
Discrete signature and its application to financeCode0
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Benchmark Results

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