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 876–900 of 6748 papers

TitleStatusHype
An Empirical Evaluation of Time-Series Feature SetsCode1
Advancing the State-of-the-Art for ECG Analysis through Structured State Space ModelsCode1
Structural Recurrent Neural Network for Traffic Speed PredictionCode1
Automatic Differentiation to Simultaneously Identify Nonlinear Dynamics and Extract Noise Probability Distributions from DataCode1
CALDA: Improving Multi-Source Time Series Domain Adaptation with Contrastive Adversarial LearningCode1
Causal Forecasting:Generalization Bounds for Autoregressive ModelsCode1
Synthesis of Realistic ECG using Generative Adversarial NetworksCode1
Classifying Sequences of Extreme Length with Constant Memory Applied to Malware DetectionCode1
TACTiS: Transformer-Attentional Copulas for Time SeriesCode1
TAnoGAN: Time Series Anomaly Detection with Generative Adversarial NetworksCode1
TCCT: Tightly-Coupled Convolutional Transformer on Time Series ForecastingCode1
Convolution-enhanced Evolving Attention NetworksCode1
Temporal Attribute Prediction via Joint Modeling of Multi-Relational Structure EvolutionCode1
An Empirical Survey of Data Augmentation for Time Series Classification with Neural NetworksCode1
Temporal Convolutional Attention Neural Networks for Time Series ForecastingCode1
An End-to-end Deep Reinforcement Learning Approach for the Long-term Short-term Planning on the Frenet SpaceCode1
Temporal Graph Neural Networks for Irregular DataCode1
Temporal Phenotyping using Deep Predictive Clustering of Disease ProgressionCode1
Testing and Estimating Structural Breaks in Time Series and Panel Data in StataCode1
Adversarial Attacks on Probabilistic Autoregressive Forecasting ModelsCode1
BolT: Fused Window Transformers for fMRI Time Series AnalysisCode1
A Bayesian neural network predicts the dissolution of compact planetary systemsCode1
From Fourier to Koopman: Spectral Methods for Long-term Time Series PredictionCode1
Next Generation Reservoir ComputingCode1
WOODS: Benchmarks for Out-of-Distribution Generalization in Time SeriesCode1
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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