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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

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Showing 601–650 of 6748 papers

TitleStatusHype
How to find a unicorn: a novel model-free, unsupervised anomaly detection method for time seriesCode1
On the difficulty of learning chaotic dynamics with RNNsCode1
catch22: CAnonical Time-series CHaracteristicsCode1
HYDRA: Competing convolutional kernels for fast and accurate time series classificationCode1
ImageFlowNet: Forecasting Multiscale Image-Level Trajectories of Disease Progression with Irregularly-Sampled Longitudinal Medical ImagesCode1
An Unsupervised Short- and Long-Term Mask Representation for Multivariate Time Series Anomaly DetectionCode1
Anytime-valid off-policy inference for contextual banditsCode1
ClaSP -- Parameter-free Time Series SegmentationCode1
Causal Recurrent Variational Autoencoder for Medical Time Series GenerationCode1
Causal structure learning from time series: Large regression coefficients may predict causal links better in practice than small p-valuesCode1
Informer: Beyond Efficient Transformer for Long Sequence Time-Series ForecastingCode1
Insights into LSTM Fully Convolutional Networks for Time Series ClassificationCode1
Instance-wise Graph-based Framework for Multivariate Time Series ForecastingCode1
Integrated multimodal artificial intelligence framework for healthcare applicationsCode1
A Physiology-Driven Computational Model for Post-Cardiac Arrest Outcome PredictionCode1
Change Point Detection in Time Series Data using Autoencoders with a Time-Invariant RepresentationCode1
Chaos as an interpretable benchmark for forecasting and data-driven modellingCode1
Changing Fashion CulturesCode1
Extraction of instantaneous frequencies and amplitudes in nonstationary time-series dataCode1
Fast, Accurate and Interpretable Time Series Classification Through RandomizationCode1
Interpretable Time Series Classification using Linear Models and Multi-resolution Multi-domain Symbolic RepresentationsCode1
Chickenpox Cases in Hungary: a Benchmark Dataset for Spatiotemporal Signal Processing with Graph Neural NetworksCode1
Adaptive Graph Convolutional Recurrent Network for Traffic ForecastingCode1
ClaSP - Time Series SegmentationCode1
Classification of Arrhythmia by Using Deep Learning with 2-D ECG Spectral Image RepresentationCode1
Classifying Sequences of Extreme Length with Constant Memory Applied to Malware DetectionCode1
A Large-Scale Annotated Multivariate Time Series Aviation Maintenance Dataset from the NGAFIDCode1
Classification of Periodic Variable Stars with Novel Cyclic-Permutation Invariant Neural NetworksCode1
FC-GAGA: Fully Connected Gated Graph Architecture for Spatio-Temporal Traffic ForecastingCode1
Joint learning of variational representations and solvers for inverse problems with partially-observed dataCode1
Explainable Multivariate Time Series Classification: A Deep Neural Network Which Learns To Attend To Important Variables As Well As Informative Time IntervalsCode1
A Generalised Signature Method for Multivariate Time Series Feature ExtractionCode1
Correlation-aware Unsupervised Change-point Detection via Graph Neural NetworksCode1
A Statistics and Deep Learning Hybrid Method for Multivariate Time Series Forecasting and Mortality ModelingCode1
Large Pre-trained time series models for cross-domain Time series analysis tasksCode1
A general framework for multi-step ahead adaptive conformal heteroscedastic time series forecastingCode1
CODiT: Conformal Out-of-Distribution Detection in Time-Series DataCode1
Latent ODEs for Irregularly-Sampled Time SeriesCode1
Explainable Deep Convolutional Candlestick LearnerCode1
Compatible deep neural network framework with financial time series data, including data preprocessor, neural network model and trading strategyCode1
DeepMoD: Deep learning for Model Discovery in noisy dataCode1
Decomposing non-stationary signals with time-varying wave-shape functionsCode1
Learning Long-Term Dependencies in Irregularly-Sampled Time SeriesCode1
Learning Signal Temporal Logic through Neural Network for Interpretable ClassificationCode1
Learning the Evolutionary and Multi-scale Graph Structure for Multivariate Time Series ForecastingCode1
The Signature Kernel is the solution of a Goursat PDECode1
Learning to Reconstruct Missing Data from Spatiotemporal Graphs with Sparse ObservationsCode1
Learning Whole Heart Mesh Generation From Patient Images For Computational SimulationsCode1
Explaining Time Series Predictions with Dynamic MasksCode1
A Time-dependent SIR model for COVID-19 with Undetectable Infected PersonsCode1
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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