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 226–250 of 6748 papers

TitleStatusHype
Axial-LOB: High-Frequency Trading with Axial AttentionCode1
Contrastive Domain Adaptation for Time-Series via Temporal MixupCode1
MHCCL: Masked Hierarchical Cluster-Wise Contrastive Learning for Multivariate Time SeriesCode1
FECAM: Frequency Enhanced Channel Attention Mechanism for Time Series ForecastingCode1
Diffusion Generative Models in Infinite DimensionsCode1
Understanding Cryptocoins Trends CorrelationsCode1
An Extreme-Adaptive Time Series Prediction Model Based on Probability-Enhanced LSTM Neural NetworksCode1
Federated Learning for 5G Base Station Traffic ForecastingCode1
Spatio-Temporal Meta-Graph Learning for Traffic ForecastingCode1
Neural Superstatistics for Bayesian Estimation of Dynamic Cognitive ModelsCode1
Understanding the Vulnerability of Skeleton-based Human Activity Recognition via Black-box AttackCode1
Finding active galactic nuclei through FinkCode1
Are we certain it's anomalous?Code1
SETAR-Tree: A Novel and Accurate Tree Algorithm for Global Time Series ForecastingCode1
Backdoor Attacks on Time Series: A Generative ApproachCode1
Advancing the State-of-the-Art for ECG Analysis through Structured State Space ModelsCode1
Wearable-based Human Activity Recognition with Spatio-Temporal Spiking Neural NetworksCode1
WindowSHAP: An Efficient Framework for Explaining Time-series Classifiers based on Shapley ValuesCode1
Efficient Integration of Multi-Order Dynamics and Internal Dynamics in Stock Movement PredictionCode1
Deep Learning for Time Series Anomaly Detection: A SurveyCode1
Automatic Change-Point Detection in Time Series via Deep LearningCode1
A Comprehensive Survey of Regression Based Loss Functions for Time Series ForecastingCode1
Learning Task-Aware Effective Brain Connectivity for fMRI Analysis with Graph Neural NetworksCode1
Spatial-Temporal Synchronous Graph Transformer network (STSGT) for COVID-19 forecastingCode1
Probabilistic Decomposition Transformer for Time Series ForecastingCode1
Show:102550
← PrevPage 10 of 270Next →
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