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 426–450 of 6748 papers

TitleStatusHype
Graph Neural Networks for Multivariate Time Series Regression with Application to Seismic DataCode1
Financial time series forecasting with multi-modality graph neural networkCode1
Role of Data Augmentation Strategies in Knowledge Distillation for Wearable Sensor DataCode1
Trading with the Momentum Transformer: An Intelligent and Interpretable ArchitectureCode1
A Statistics and Deep Learning Hybrid Method for Multivariate Time Series Forecasting and Mortality ModelingCode1
Scale-Aware Neural Architecture Search for Multivariate Time Series ForecastingCode1
Multi-Modal Temporal Attention Models for Crop Mapping from Satellite Time SeriesCode1
Parameter Efficient Deep Probabilistic ForecastingCode1
Dynamic Graph Learning-Neural Network for Multivariate Time Series ModelingCode1
ES-dRNN: A Hybrid Exponential Smoothing and Dilated Recurrent Neural Network Model for Short-Term Load ForecastingCode1
Anomaly Detection of Wind Turbine Time Series using Variational Recurrent AutoencodersCode1
Simulation platform for pattern recognition based on reservoir computing with memristor networksCode1
Conformal Time-series ForecastingCode1
Self-supervised Autoregressive Domain Adaptation for Time Series DataCode1
Improving Deep Learning Interpretability by Saliency Guided TrainingCode1
Amercing: An Intuitive, Elegant and Effective Constraint for Dynamic Time WarpingCode1
Neural network stochastic differential equation models with applications to financial data forecastingCode1
tsflex: flexible time series processing & feature extractionCode1
Interpreting Machine Learning Models for Room Temperature Prediction in Non-domestic BuildingsCode1
Modeling Irregular Time Series with Continuous Recurrent UnitsCode1
Causal Forecasting:Generalization Bounds for Autoregressive ModelsCode1
HiRID-ICU-Benchmark -- A Comprehensive Machine Learning Benchmark on High-resolution ICU DataCode1
Towards Generating Real-World Time Series DataCode1
Learning Graph Neural Networks for Multivariate Time Series Anomaly DetectionCode1
TimeVAE: A Variational Auto-Encoder for Multivariate Time Series GenerationCode1
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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