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 44014450 of 6748 papers

TitleStatusHype
Interpretable System Identification and Long-term Prediction on Time-Series Data0
Interpretable Time Series Clustering Using Local Explanations0
Learning Disentangled Representations for Time Series0
Interpretable Water Level Forecaster with Spatiotemporal Causal Attention Mechanisms0
Interpretable Vector AutoRegressions with Exogenous Time Series0
Interpreting 16S metagenomic data without clustering to achieve sub-OTU resolution0
Interpreting a Recurrent Neural Network's Predictions of ICU Mortality Risk0
Interpreting intermediate convolutional layers of generative CNNs trained on waveforms0
Interpreting intermediate convolutional layers in unsupervised acoustic word classification0
Inter-time segment information sharing for non-homogeneous dynamic Bayesian networks0
Interval Forecasting of Electricity Demand: A Novel Bivariate EMD-based Support Vector Regression Modeling Framework0
Intra-day Activity Better Predicts Chronic Conditions0
Intraday Functional PCA Forecasting of Cryptocurrency Returns0
Intraday trading strategy based on time series and machine learning for Chinese stock market0
Intra-domain and cross-domain transfer learning for time series data -- How transferable are the features?0
Intrinsic Anomaly Detection for Multi-Variate Time Series0
Introducing Data Primitives: Data Formats for the SKED Framework0
Introducing Randomized High Order Fuzzy Cognitive Maps as Reservoir Computing Models: A Case Study in Solar Energy and Load Forecasting0
Market-Based Price Autocorrelation0
Adversarial Attacks on Time-Series Intrusion Detection for Industrial Control Systems0
Invariant Factorization Of Time-Series0
Invariants of multidimensional time series based on their iterated-integral signature0
Long Short-Term Memory Neural Networks for False Information Attack Detection in Software-Defined In-Vehicle Network0
Inverse Moment Methods for Sufficient Forecasting using High-Dimensional Predictors0
Inverse and Quanto Inverse Options in a Black-Scholes World0
Investigating echo state networks dynamics by means of recurrence analysis0
Investigating Sindy As a Tool For Causal Discovery In Time Series Signals0
Investigating Temporal Convolutional Neural Networks for Satellite Image Time Series Classification: A survey0
Investigating the genomic background of CRISPR-Cas genomes for CRISPR-based antimicrobials0
Investigating the impact of autocorrelation on time-varying connectivity0
Investigation of Flash Crash via Topological Data Analysis0
Investigation of Proper Orthogonal Decomposition for Echo State Networks0
Investigation on the use of Hidden-Markov Models in automatic transcription of music0
IoT Network Behavioral Fingerprint Inference with Limited Network Trace for Cyber Investigation: A Meta Learning Approach0
IRMAC: Interpretable Refined Motifs in Binary Classification for Smart Grid Applications0
Irregularly-Sampled Time Series Modeling with Spline Networks0
Ischemic Stroke Lesion Prediction using imbalanced Temporal Deep Gaussian Process (iTDGP)0
Isolating the impact of trading on grid frequency fluctuations0
Is the Indian Stock Market efficient - A comprehensive study of Bombay Stock Exchange Indices0
Is type 1 diabetes a chaotic phenomenon?0
IT2CFNN: An Interval Type-2 Correlation-Aware Fuzzy Neural Network to Construct Non-Separable Fuzzy Rules with Uncertain and Adaptive Shapes for Nonlinear Function Approximation0
Iterative Bilinear Temporal-Spectral Fusion for Unsupervised Representation Learning in Time Series0
Iteratively reweighted adaptive lasso for conditional heteroscedastic time series with applications to AR-ARCH type processes0
Layer-wise Relevance Propagation for Echo State Networks applied to Earth System Variability0
It's a super deal -- train recurrent network on noisy data and get smooth prediction free0
It's Time to Consider "Time" when Evaluating Recommender-System Algorithms [Proposal]0
Jacobian Granger Causal Neural Networks for Analysis of Stationary and Nonstationary Data0
Jerk-Aware Video Acceleration Magnification0
Jiffy: A Convolutional Approach to Learning Time Series Similarity0
Joint cardiac T_1 mapping and cardiac function estimation using a deep manifold framework0
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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