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 2751–2775 of 6748 papers

TitleStatusHype
When Complexity Is Good: Do We Need Recurrent Deep Learning For Time Series Outlier Detection?—0
A Systematic Evaluation of Domain Adaptation Algorithms On Time Series Data—0
Selective Cross-Domain Consistency Regularization for Time Series Domain Generalization—0
Neural Markov Controlled SDE: Stochastic Optimization for Continuous-Time Data—0
A Study of Aggregation of Long Time-series Input for LSTM Neural Networks—0
Multi-Task Processes—0
Context-invariant, multi-variate time series representations—0
Huber Additive Models for Non-stationary Time Series Analysis—0
Taking ROCKET on an efficiency mission: A distributed solution for fast and accurate multivariate time series classification—0
Loss meta-learning for forecasting—0
Cross-Camera Human Motion Transfer by Time Series AnalysisCode0
IIT-GAN: Irregular and Intermittent Time-series Synthesis with Generative Adversarial Networks—0
Coherence-based Label Propagation over Time Series for Accelerated Active Learning—0
Sample Complexity of the Robust LQG Regulator with Coprime Factors Uncertainty—0
ACCTS: an Adaptive Model Training Policy for Continuous Classification of Time Series—0
Iterative Bilinear Temporal-Spectral Fusion for Unsupervised Representation Learning in Time Series—0
Cluster-based Feature Importance Learning for Electronic Health Record Time-series—0
TAMP-S2GCNets: Coupling Time-Aware Multipersistence Knowledge Representation with Spatio-Supra Graph Convolutional Networks for Time-Series Forecasting—0
SCformer: Segment Correlation Transformer for Long Sequence Time Series Forecasting—0
Variational Inference for Continuous-Time Switching Dynamical Systems—0
Evaluating the Robustness of Time Series Anomaly and Intrusion Detection Methods against Adversarial Attacks—0
Time Delay Estimation of Traffic Congestion Based on Statistical Causality—0
TRAKR – A reservoir-based tool for fast and accurate classification of neural time-series patterns—0
Less is more: Selecting the right benchmarking set of data for time series classification—0
CDPS: Constrained DTW-Preserving Shapelets—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