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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 2701–2725 of 6748 papers

TitleStatusHype
Topological Data Analysis (TDA) Techniques Enhance Hand Pose Classification from ECoG Neural Recordings—0
EnsembleNTLDetect: An Intelligent Framework for Electricity Theft Detection in Smart Grid—0
Hankel-structured Tensor Robust PCA for Multivariate Traffic Time Series Anomaly Detection—0
Subspace Change-Point Detection via Low-Rank Matrix Factorisation—0
Joint Normality Test Via Two-Dimensional Projection—0
Cross-modal Knowledge Distillation for Vision-to-Sensor Action RecognitionCode0
Generative Pre-Trained Transformer for Cardiac Abnormality Detection—0
Automated Testing of AI Models—0
Darts: User-Friendly Modern Machine Learning for Time Series—0
Predictive Maintenance for General Aviation Using Convolutional Transformers—0
A Meta-learning Approach to Reservoir Computing: Time Series Prediction with Limited Data—0
5G Traffic Prediction with Time Series Analysis—0
PRRS Outbreak Prediction via Deep Switching Auto-Regressive Factorization Modeling—0
Time Series Forecasting Using Manifold Learning—0
EEG functional connectivity and deep learning for automatic diagnosis of brain disorders: Alzheimer's disease and schizophrenia—0
Sentinel 2 Time Series Analysis with 3D Feature Pyramid Network and Time Domain Class Activation Intervals for Crop MappingCode0
An Accurate Smartphone Battery Parameter Calibration Using Unscented Kalman Filter—0
Generative Optimization Networks for Memory Efficient Data GenerationCode0
Bayesian autoregressive spectral estimation—0
Attention Augmented Convolutional Transformer for Tabular Time-series—0
Networked Time Series Prediction with Incomplete Data via Generative Adversarial Network—0
Overcoming limited battery data challenges: A coupled neural network approach—0
Interpreting intermediate convolutional layers in unsupervised acoustic word classification—0
RapidAI4EO: A Corpus for Higher Spatial and Temporal Reasoning—0
HYPPO: A Surrogate-Based Multi-Level Parallelism Tool for Hyperparameter Optimization—0
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All datasetsPhysioNet Challenge 2012Speech CommandsVentilator Pressure Prediction

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