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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 2251–2275 of 6748 papers

TitleStatusHype
Subspace Change-Point Detection via Low-Rank Matrix Factorisation—0
Sentinel 2 Time Series Analysis with 3D Feature Pyramid Network and Time Domain Class Activation Intervals for Crop MappingCode0
EEG functional connectivity and deep learning for automatic diagnosis of brain disorders: Alzheimer's disease and schizophrenia—0
Predictive Maintenance for General Aviation Using Convolutional Transformers—0
PRRS Outbreak Prediction via Deep Switching Auto-Regressive Factorization Modeling—0
Darts: User-Friendly Modern Machine Learning for Time Series—0
Generative Pre-Trained Transformer for Cardiac Abnormality Detection—0
A Meta-learning Approach to Reservoir Computing: Time Series Prediction with Limited Data—0
5G Traffic Prediction with Time Series Analysis—0
Time Series Forecasting Using Manifold Learning—0
Automated Testing of AI Models—0
An Accurate Smartphone Battery Parameter Calibration Using Unscented Kalman Filter—0
Generative Optimization Networks for Memory Efficient Data GenerationCode0
Anomaly Transformer: Time Series Anomaly Detection with Association DiscrepancyCode2
Overcoming limited battery data challenges: A coupled neural network approach—0
Bayesian autoregressive spectral estimation—0
RapidAI4EO: A Corpus for Higher Spatial and Temporal Reasoning—0
Attention Augmented Convolutional Transformer for Tabular Time-series—0
Networked Time Series Prediction with Incomplete Data via Generative Adversarial Network—0
Interpreting intermediate convolutional layers in unsupervised acoustic word classification—0
Truth-Conditional Captioning of Time Series DataCode1
Cross-Modal Virtual Sensing for Combustion Instability Monitoring—0
HYPPO: A Surrogate-Based Multi-Level Parallelism Tool for Hyperparameter Optimization—0
Causality and Generalizability: Identifiability and Learning Methods—0
State-Space Models Win the IEEE DataPort Competition on Post-covid Day-ahead Electricity Load Forecasting—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