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 1726–1750 of 6748 papers

TitleStatusHype
Hierarchical Linear Dynamical System for Representing Notes from Recorded Audio—0
Architectural Optimization and Feature Learning for High-Dimensional Time Series Datasets—0
ONE-NAS: An Online NeuroEvolution based Neural Architecture Search for Time Series Forecasting—0
Taming the Long Tail of Deep Probabilistic Forecasting—0
Meta-path Analysis on Spatio-Temporal Graphs for Pedestrian Trajectory PredictionCode0
Regularized Bilinear Discriminant Analysis for Multivariate Time Series Data—0
Mental State Classification Using Multi-graph Features—0
Capturing Actionable Dynamics with Structured Latent Ordinary Differential EquationsCode0
Novel techniques for improving NNetEn entropy calculation for short and noisy time series—0
Stacked Residuals of Dynamic Layers for Time Series Anomaly Detection—0
Long-Term Missing Value Imputation for Time Series Data Using Deep Neural Networks—0
Integrated multimodal artificial intelligence framework for healthcare applicationsCode1
Evolutionary scheduling of university activities based on consumption forecasts to minimise electricity costsCode0
Sequential asset ranking in nonstationary time series—0
Predicting the impact of treatments over time with uncertainty aware neural differential equationsCode0
Robust Probabilistic Time Series ForecastingCode1
Simulating Network Paths with Recurrent Buffering Units—0
Deep Recurrent Modelling of Granger Causality with Latent Confounding—0
Preformer: Predictive Transformer with Multi-Scale Segment-wise Correlations for Long-Term Time Series ForecastingCode1
A Differential Attention Fusion Model Based on Transformer for Time Series Forecasting—0
Amortised Likelihood-free Inference for Expensive Time-series Simulators with Signatured Ratio Estimation—0
Nowcasting the Financial Time Series with Streaming Data Analytics under Apache Spark—0
NeuroView-RNN: It's About Time—0
NetRCA: An Effective Network Fault Cause Localization Algorithm—0
Neural Generalised AutoRegressive Conditional Heteroskedasticity—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