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 5401–5450 of 6748 papers

TitleStatusHype
A topological analysis of cointegrated data: a Z24 Bridge case study—0
A Trainable Reconciliation Method for Hierarchical Time-Series—0
A Transfer-Learning Based Ensemble Architecture for ECG Signal Classification—0
A Transformer-based Deep Learning Algorithm to Auto-record Undocumented Clinical One-Lung Ventilation Events—0
A transformer-based model for default prediction in mid-cap corporate markets—0
A Tree-structure Convolutional Neural Network for Temporal Features Exaction on Sensor-based Multi-resident Activity Recognition—0
Attend and Diagnose: Clinical Time Series Analysis using Attention Models—0
Attention Augmented Convolutional Transformer for Tabular Time-series—0
Attention-based Neural Load Forecasting: A Dynamic Feature Selection Approach—0
Attention-based Neural Network for Driving Environment Complexity Perception—0
AttentionFlow: Visualising Influence in Networks of Time Series—0
Attention Is Not Enough: Mitigating the Distribution Discrepancy in Asynchronous Multimodal Sequence Fusion—0
Attention Mechanism for Multivariate Time Series Recurrent Model Interpretability Applied to the Ironmaking Industry—0
Attentive Gaussian processes for probabilistic time-series generation—0
Attentive Weakly Supervised land cover mapping for object-based satellite image time series data with spatial interpretation—0
A Two-layer Approach for Estimating Behind-the-Meter PV Generation Using Smart Meter Data—0
A Two-Stage Coordinative Zonal Volt/VAR Control Scheme for Distribution Systems with High Inverter-based Resources—0
A Two-Step Framework for Arbitrage-Free Prediction of the Implied Volatility Surface—0
A Two-Way Transformed Factor Model for Matrix-Variate Time Series—0
Augmented Bilinear Network for Incremental Multi-Stock Time-Series Classification—0
Augmenting Physiological Time Series Data: A Case Study for Sleep Apnea Detection—0
Augmenting transferred representations for stock classification—0
A Unified Framework for Long Range and Cold Start Forecasting of Seasonal Profiles in Time Series—0
A unified framework of epidemic spreading prediction by empirical mode decomposition based ensemble learning techniques—0
A unified machine learning approach to time series forecasting applied to demand at emergency departments—0
A Unified Method for First and Third Person Action Recognition—0
A Unified SVM Framework for Signal Estimation—0
A user-centric model of voting intention from Social Media—0
Autism Spectrum Disorder Classification using Graph Kernels on Multidimensional Time Series—0
AutoAI-TS: AutoAI for Time Series Forecasting—0
AutoCTS: Automated Correlated Time Series Forecasting -- Extended Version—0
Autoencoder based Anomaly Detection and Explained Fault Localization in Industrial Cooling Systems—0
Autoencoder-based time series clustering with energy applications—0
Autoencoding Conditional GAN for Portfolio Allocation Diversification—0
Autoencoding Time Series for Visualisation—0
Automated Antenna Testing Using Encoder-Decoder-based Anomaly Detection—0
Automated Detection of Left Ventricle in Arterial Input Function Images for Inline Perfusion Mapping using Deep Learning: A study of 15,000 Patients—0
Automated Diagnosis of Epilepsy Employing Multifractal Detrended Fluctuation Analysis Based Features—0
Automated Few-Shot Time Series Forecasting based on Bi-level Programming—0
Automated Label Generation for Time Series Classification with Representation Learning: Reduction of Label Cost for Training—0
Automated Machine Learning on Big Data using Stochastic Algorithm Tuning—0
Automated Mobility Context Detection with Inertial Signals—0
Automated Model Selection for Time-Series Anomaly Detection—0
Automated Polysomnography Analysis for Detection of Non-Apneic and Non-Hypopneic Arousals using Feature Engineering and a Bidirectional LSTM Network—0
Automated Real-time Anomaly Detection in Human Trajectories using Sequence to Sequence Networks—0
Automated Testing of AI Models—0
Automatic Classification of Irregularly Sampled Time Series with Unequal Lengths: A Case Study on Estimated Glomerular Filtration Rate—0
Automatic Construction of a Recurrent Neural Network based Classifier for Vehicle Passage Detection—0
Automatic deep learning for trend prediction in time series data—0
Automatic Detection of Interplanetary Coronal Mass Ejections in Solar Wind In Situ Data—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