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 2326–2350 of 6748 papers

TitleStatusHype
3KG: Contrastive Learning of 12-Lead Electrocardiograms using Physiologically-Inspired Augmentations—0
Experimentally testable whole brain manifolds that recapitulate behavior—0
Changepoint Analysis of Topic Proportions in Temporal Text Data—0
Change of persistence in European electricity spot prices—0
An overview and comparative analysis of Recurrent Neural Networks for Short Term Load Forecasting—0
A NOVEL VARIATIONAL FAMILY FOR HIDDEN NON-LINEAR MARKOV MODELS—0
Challenges with Extreme Class-Imbalance and Temporal Coherence: A Study on Solar Flare Data—0
The Adaptive Doubly Robust Estimator for Policy Evaluation in Adaptive Experiments and a Paradox Concerning Logging Policy—0
Experimental demonstration of bandwidth enhancement in photonic time delay reservoir computing—0
Expert Aggregation for Financial Forecasting—0
Explainable AI for tailored electricity consumption feedback -- an experimental evaluation of visualizations—0
Challenges in Forecasting Malicious Events from Incomplete Data—0
Nonlinear Evolution via Spatially-Dependent Linear Dynamics for Electrophysiology and Calcium Data—0
Aiding Long-Term Investment Decisions with XGBoost Machine Learning Model—0
Challenges and approaches to time-series forecasting in data center telemetry: A Survey—0
CHALLENGER: Training with Attribution Maps—0
A Novel Trend Symbolic Aggregate Approximation for Time Series—0
EXIT: Extrapolation and Interpolation-based Neural Controlled Differential Equations for Time-series Classification and Forecasting—0
CGT: Clustered Graph Transformer for Urban Spatio-temporal Prediction—0
A Novel Time-Varying Spectral Filtering Algorithm for Reconstruction of Motion Artifact Corrupted Heart Rate Signals During Intense Physical Activities Using a Wearable Photoplethysmogram Sensor—0
A novel stochastic model based on echo state networks for hydrological time series forecasting—0
Central and Non-central Limit Theorems arising from the Scattering Transform and its Neural Activation Generalization—0
Cellular reprogramming dynamics follow a simple one-dimensional reaction coordinate—0
A Hybrid Residual Dilated LSTM end Exponential Smoothing Model for Mid-Term Electric Load Forecasting—0
Expectation Propagation in Gaussian Process Dynamical Systems: Extended Version—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