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 1551–1575 of 6748 papers

TitleStatusHype
Deep learning for structural health monitoring: An application to heritage structures—0
Time series quantile regression using random forests—0
Topological biomarkers for real-time detection of epileptic seizures—0
Reservoir Computing via Quantum Recurrent Neural Networks—0
Collaborative Multiobjective Evolutionary Algorithms in search of better Pareto Fronts. An application to trading systems—0
Modeling Temporal Data as Continuous Functions with Stochastic Process Diffusion—0
Boosted p-Values for High-Dimensional Vector Autoregression—0
Robust Time Series Chain Discovery with Incremental Nearest Neighbors—0
On Estimation and Inference of Large Approximate Dynamic Factor Models via the Principal Component Analysis—0
Embed and Emulate: Learning to estimate parameters of dynamical systems with uncertainty quantificationCode0
Demo: LE3D: A Privacy-preserving Lightweight Data Drift Detection Framework—0
MUSTACHE: Multi-Step-Ahead Predictions for Cache Eviction—0
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
Infinite-Dimensional Adaptive Boundary Observer for Inner-Domain Temperature Estimation of 3D Electrosurgical Processes using Surface Thermography Sensing—0
HFN: Heterogeneous Feature Network for Multivariate Time Series Anomaly Detection—0
Recurrent Neural Networks and Universal Approximation of Bayesian Filters—0
A novel approach to quantify volatility prediction—0
MambaNet: A Hybrid Neural Network for Predicting the NBA Playoffs—0
Denoising neural networks for magnetic resonance spectroscopy—0
Ensemble transport smoothing. Part I: Unified frameworkCode0
Variational Inference Aided Estimation of Time Varying Channels—0
AtOMICS: A neural network-based Automated Optomechanical Intelligent Coupling System for testing and characterization of silicon photonics chiplets—0
Uncertainty-DTW for Time Series and SequencesCode0
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All datasetsPhysioNet Challenge 2012Speech CommandsVentilator Pressure Prediction

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