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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 801–850 of 6748 papers

TitleStatusHype
A Graph Neural Networks based Framework for Topology-Aware Proactive SLA Management in a Latency Critical NFV Application Use-case—0
Driver Maneuver Detection and Analysis using Time Series Segmentation and Classification—0
Variance of entropy for testing time-varying regimes with an application to meme stocks—0
Detecting Elevated Air Pollution Levels by Monitoring Web Search Queries: Deep Learning-Based Time Series Forecasting—0
Deep Learning for Time Series Anomaly Detection: A SurveyCode1
Bayesian Neural Networks for Macroeconomic Analysis—0
Active queue management: First steps toward a new control-theoretic viewpoint—0
Towards Global Crop Maps with Transfer Learning—0
Motif-guided Time Series Counterfactual Explanations—0
Dynamic Interpretable Change Point Detection—0
Quantum Persistent Homology for Time Series—0
Privacy Meets Explainability: A Comprehensive Impact Benchmark—0
Reduced Order Probabilistic Emulation for Physics-Based Thermosphere ModelsCode0
TimeKit: A Time-series Forecasting-based Upgrade Kit for Collaborative Filtering—0
FIXED: Frustratingly Easy Domain Generalization with Mixup—0
Minimax Concave Penalty Regularized Adaptive System Identification—0
Latent Neural ODE for Integrating Multi-timescale measurements in Smart Distribution Grids—0
Automatic Change-Point Detection in Time Series via Deep LearningCode1
A Synthetic Dataset for 5G UAV Attacks Based on Observable Network Parameters—0
A Comprehensive Survey of Regression Based Loss Functions for Time Series ForecastingCode1
Accurate and Reliable Methods for 5G UAV Jamming Identification With Calibrated Uncertainty—0
Discovering ordinary differential equations that govern time-series—0
Deep learning for structural health monitoring: An application to heritage structures—0
Topological biomarkers for real-time detection of epileptic seizures—0
Reservoir Computing via Quantum Recurrent Neural Networks—0
Modeling Temporal Data as Continuous Functions with Stochastic Process Diffusion—0
Boosted p-Values for High-Dimensional Vector Autoregression—0
Time series quantile regression using random forests—0
Collaborative Multiobjective Evolutionary Algorithms in search of better Pareto Fronts. An application to trading systems—0
MUSTACHE: Multi-Step-Ahead Predictions for Cache Eviction—0
On Estimation and Inference of Large Approximate Dynamic Factor Models via the Principal Component Analysis—0
Demo: LE3D: A Privacy-preserving Lightweight Data Drift Detection Framework—0
Robust Time Series Chain Discovery with Incremental Nearest Neighbors—0
Embed and Emulate: Learning to estimate parameters of dynamical systems with uncertainty quantificationCode0
Physics-inspired machine learning for power grid frequency modelling—0
Geodesic Sinkhorn for Fast and Accurate Optimal Transport on Manifolds—0
Evaluating Impact of Social Media Posts by Executives on Stock PricesCode0
Recurrent Neural Networks and Universal Approximation of Bayesian Filters—0
Infinite-Dimensional Adaptive Boundary Observer for Inner-Domain Temperature Estimation of 3D Electrosurgical Processes using Surface Thermography Sensing—0
Learning Task-Aware Effective Brain Connectivity for fMRI Analysis with Graph Neural NetworksCode1
HFN: Heterogeneous Feature Network for Multivariate Time Series Anomaly Detection—0
A novel approach to quantify volatility prediction—0
Spatial-Temporal Synchronous Graph Transformer network (STSGT) for COVID-19 forecastingCode1
Variational Inference Aided Estimation of Time Varying Channels—0
Ensemble transport smoothing. Part I: Unified frameworkCode0
Denoising neural networks for magnetic resonance spectroscopy—0
MambaNet: A Hybrid Neural Network for Predicting the NBA Playoffs—0
Diffusion models for missing value imputation in tabular dataCode1
Probabilistic Decomposition Transformer for Time Series ForecastingCode1
Uncertainty-DTW for Time Series and SequencesCode0
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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