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 3201–3250 of 6748 papers

TitleStatusHype
Normalized multivariate time series causality analysis and causal graph reconstruction—0
Sequential convolutional network for behavioral pattern extraction in gait recognition—0
A Feature Selection Method for Multi-Dimension Time-Series Data—0
Scalable Predictive Time-Series Analysis of COVID-19: Cases and Fatalities—0
Survey on Modeling Intensity Function of Hawkes Process Using Neural Models—0
Time series analysis with dynamic law exploration—0
Enhancing predictive skills in physically-consistent way: Physics Informed Machine Learning for Hydrological Processes—0
Real-time NLOS/LOS Identification for Smartphone-based Indoor Positioning System using WiFi RTT and RSS—0
Principal Component Density Estimation for Scenario Generation Using Normalizing Flows—0
Aedes-AI: Neural Network Models of Mosquito Abundance—0
A windowed correlation based feature selection method to improve time series prediction of dengue fever cases—0
A Comparative Study of Using Spatial-Temporal Graph Convolutional Networks for Predicting Availability in Bike Sharing Schemes—0
Winterization of Texan power system infrastructure is profitable but risky—0
Mixture Models for the Analysis, Edition, and Synthesis of Continuous Time Series—0
3KG: Contrastive Learning of 12-Lead Electrocardiograms using Physiologically-Inspired Augmentations—0
Using CNNs for AD classification based on spatial correlation of BOLD signals during the observation—0
A geometric approach to conditioning belief functions—0
Forecasting The JSE Top 40 Using Long Short-Term Memory Networks—0
Modeling biological networks: from single gene systems to large microbial communities—0
Interpreting intermediate convolutional layers of generative CNNs trained on waveforms—0
Inference of Upcoming Human Grasp Using EMG During Reach-to-Grasp Movement—0
Aiding Long-Term Investment Decisions with XGBoost Machine Learning Model—0
SALAD: Self-Adaptive Lightweight Anomaly Detection for Real-time Recurrent Time Series—0
Recursive input and state estimation: A general framework for learning from time series with missing data—0
Probabilistic water demand forecasting using quantile regression algorithms—0
Integrating Domain Knowledge in Data-driven Earth Observation with Process Convolutions—0
Explorative Data Analysis of Time Series based AlgorithmFeatures of CMA-ES Variants—0
Viking: Variational Bayesian Variance Tracking—0
Demographic-Guided Attention in Recurrent Neural Networks for Modeling Neuropathophysiological Heterogeneity—0
Tracking agitation in people living with dementia in a care environment—0
Process Outcome Prediction: CNN vs. LSTM (with Attention)—0
Forecasting COVID-19 Counts At A Single Hospital: A Hierarchical Bayesian ApproachCode0
Underwater dual-magnification imaging for automated lake plankton monitoring—0
Bayesian Optimisation for a Biologically Inspired Population Neural Network—0
LioNets: A Neural-Specific Local Interpretation Technique Exploiting Penultimate Layer InformationCode0
A Bayesian analysis of gain-loss asymmetry—0
A Fast Evidential Approach for Stock Forecasting—0
Analysis of bank leverage via dynamical systems and deep neural networks—0
Boosted Embeddings for Time Series Forecasting—0
Deep Transformer Networks for Time Series Classification: The NPP Safety Case—0
Granger Causality Based Hierarchical Time Series Clustering for State Estimation—0
Large-scale nonlinear Granger causality for inferring directed dependence from short multivariate time-series data—0
Flow-based Spatio-Temporal Structured Prediction of Motion DynamicsCode0
Neural Network for Weighted Signal Temporal Logic—0
Fingerprint Presentation Attack Detection utilizing Time-Series, Color Fingerprint Captures—0
CARRNN: A Continuous Autoregressive Recurrent Neural Network for Deep Representation Learning from Sporadic Temporal Data—0
Market Regime Detection via Realized Covariances: A Comparison between Unsupervised Learning and Nonlinear Models—0
Evaluation of Time Series Forecasting Models for Estimation of PM2.5 Levels in Air—0
Min(d)ing the President: A text analytic approach to measuring tax news—0
Bootstrap Inference for Hawkes and General Point Processes—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