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 2351–2400 of 6748 papers

TitleStatusHype
Cell cycle time series gene expression data encoded as cyclic attractors in Hopfield systems—0
A novel spectral method for inferring general diploid selection from time series genetic data—0
CellCycleGAN: Spatiotemporal Microscopy Image Synthesis of Cell Populations using Statistical Shape Models and Conditional GANs—0
A Novel Sparse Bayesian Learning and Its Application to Fault Diagnosis for Multistation Assembly Systems—0
A hybrid neuro--wavelet predictor for QoS control and stability—0
Exploring System Performance of Continual Learning for Mobile and Embedded Sensing Applications—0
CDPS: Constrained DTW-Preserving Shapelets—0
A Novel Site-Agnostic Multimodal Deep Learning Model to Identify Pro-Eating Disorder Content on Social Media—0
Exploring Spatial-Temporal Variations of Public Discourse on Social Media: A Case Study on the First Wave of the Coronavirus Pandemic in Italy—0
Entropy Analysis of Financial Time Series—0
Estimation and Inference in High-Dimensional Panel Data Models with Interactive Fixed Effects—0
Entropic Dynamic Time Warping Kernels for Co-evolving Financial Time Series Analysis—0
Entanglement-Embedded Recurrent Network Architecture: Tensorized Latent State Propagation and Chaos Forecasting—0
Adaptive deep learning for nonlinear time series models—0
Exploring Strategies for Classification of External Stimuli Using Statistical Features of the Plant Electrical Response—0
Exposing the Impact of GenAI for Cybercrime: An Investigation into the Dark Side—0
Extension of the Lagrange multiplier test for error cross-section independence to large panels with non normal errors—0
Error Autocorrelation Objective Function for Improved System Modeling—0
Cause-Effect Preservation and Classification using Neurochaos Learning—0
Entropy and Transfer Entropy: The Dow Jones and the build up to the 1997 Asian Crisis—0
Entropy Approximation by Machine Learning Regression: Application for Irregularity Evaluation of Images in Remote Sensing—0
Entropy-based Discovery of Summary Causal Graphs in Time Series—0
Exploring Financial Networks Using Quantile Regression and Granger Causality—0
Epidemic parameters for COVID-19 in several regions of India—0
Epileptic Seizure Detection: A Deep Learning Approach—0
Epileptic Seizure Prediction: A Semi-Dilated Convolutional Neural Network Architecture—0
Equipment Health Assessment: Time Series Analysis for Wind Turbine Performance—0
Equivalence relations and L^p distances between time series with application to the Black Summer Australian bushfires—0
Ergodic characterization of non-ergodic anomalous diffusion processes—0
E-RNN: Design Optimization for Efficient Recurrent Neural Networks in FPGAs—0
Error-bounded Approximate Time Series Joins Using Compact Dictionary Representations of Time Series—0
Error-feedback stochastic modeling strategy for time series forecasting with convolutional neural networks—0
Ensembles of Randomized NNs for Pattern-based Time Series Forecasting—0
Cause-effect inference through spectral independence in linear dynamical systems: theoretical foundations—0
Central and Non-central Limit Theorems arising from the Scattering Transform and its Neural Activation Generalization—0
Exploring grid topology reconfiguration using a simple deep reinforcement learning approach—0
Estimación del Exponente de Hurst en Flujos de Tráfico Autosimilares—0
Estimating 3D Trajectories from 2D Projections via Disjunctive Factored Four-Way Conditional Restricted Boltzmann Machines—0
CGT: Clustered Graph Transformer for Urban Spatio-temporal Prediction—0
Estimating activity cycles with probabilistic methods II. The Mount Wilson Ca H&K data—0
Estimating and backtesting risk under heavy tails—0
Estimating covariant Lyapunov vectors from data—0
Estimating Driver Personality Traits from On-Road Driving Data—0
Estimating Gradual-Emotional Behavior in One-Minute Videos with ESNs—0
Estimating Granger Causality with Unobserved Confounders via Deep Latent-Variable Recurrent Neural Network—0
Estimating information in time-varying signals—0
Estimating Network Structure from Incomplete Event Data—0
Challenges in Forecasting Malicious Events from Incomplete Data—0
A Novel Multi-Stage Training Approach for Human Activity Recognition from Multimodal Wearable Sensor Data Using Deep Neural Network—0
Causal Triple Attention Time Series 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