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 1401–1425 of 6748 papers

TitleStatusHype
The Functional Wiener Filter—0
Behave-XAI: Deep Explainable Learning of Behavioral Representational Data—0
Unsupervised 4D LiDAR Moving Object Segmentation in Stationary Settings with Multivariate Occupancy Time SeriesCode0
Time series Forecasting to detect anomalous behaviours in Multiphase Flow Meters—0
Label-Efficient Interactive Time-Series Anomaly Detection—0
Investigating Sindy As a Tool For Causal Discovery In Time Series Signals—0
Deep Temporal Contrastive Clustering—0
Robustifying Markowitz—0
Semi-supervised multiscale dual-encoding method for faulty traffic data detection—0
Anomaly detection in laser-guided vehicles' batteries: a case study—0
Modeling Nonlinear Dynamics in Continuous Time with Inductive Biases on Decay Rates and/or Frequencies—0
Modeling Time-Series and Spatial Data for Recommendations and Other Applications—0
Streaming Traffic Flow Prediction Based on Continuous Reinforcement Learning—0
Security and Interpretability in Automotive Systems—0
Simple Yet Surprisingly Effective Training Strategies for LSTMs in Sensor-Based Human Activity Recognition—0
Few-shot human motion prediction for heterogeneous sensorsCode0
Machine Learning with Probabilistic Law Discovery: A Concise Introduction—0
Temporal Disaggregation of the Cumulative Grass Growth—0
Is it worth it? Comparing six deep and classical methods for unsupervised anomaly detection in time seriesCode0
A Query-Response Causal Analysis of Reaction Events in Biochemical Reaction Networks—0
Dynamic Molecular Graph-based Implementation for Biophysical Properties Prediction—0
A Pattern Discovery Approach to Multivariate Time Series Forecasting—0
Contextually Enhanced ES-dRNN with Dynamic Attention for Short-Term Load ForecastingCode0
Page time and the order parameter for a consciousness state—0
Reservoir Computing Using Complex Systems—0
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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