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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 1326–1350 of 6748 papers

TitleStatusHype
StaDRe and StaDRo: Reliability and Robustness Estimation of ML-based Forecasting using Statistical Distance MeasuresCode1
Self-Supervised Contrastive Pre-Training For Time Series via Time-Frequency ConsistencyCode2
Plotly-Resampler: Effective Visual Analytics for Large Time SeriesCode3
A Deep Learning Approach for the Segmentation of Electroencephalography Data in Eye Tracking ApplicationsCode1
Uncertainty-aware Evaluation of Time-Series Classification for Online Handwriting Recognition with Domain Shift—0
Domain Generalization via Selective Consistency Regularization for Time Series Classification—0
Deep Neural Imputation: A Framework for Recovering Incomplete Brain Recordings—0
User Engagement in Mobile Health Applications—0
Cyclocopula Technique to Study the Relationship Between Two Cyclostationary Time Series with Fractional Brownian Motion Errors—0
Learning with little mixing—0
When Rigidity Hurts: Soft Consistency Regularization for Probabilistic Hierarchical Time Series ForecastingCode1
Continuous-Time Modeling of Counterfactual Outcomes Using Neural Controlled Differential EquationsCode1
MAGIC: Microlensing Analysis Guided by Intelligent ComputationCode1
Closed-Form Diffeomorphic Transformations for Time Series AlignmentCode1
Conformal prediction set for time-seriesCode1
Evaluating Short-Term Forecasting of Multiple Time Series in IoT EnvironmentsCode0
Calibrating Agent-based Models to Microdata with Graph Neural Networks—0
Deep Isolation Forest for Anomaly DetectionCode1
Improving Solar Flare Prediction by Time Series Outlier Detection—0
Residual-based physics-informed transfer learning: A hybrid method for accelerating long-term CFD simulations via deep learning—0
Using generalized additive models to decompose time series and waveforms, and dissect heart-lung interaction physiologyCode0
Robust Time Series Denoising with Learnable Wavelet Packet Transform—0
Efficient recurrent architectures through activity sparsity and sparse back-propagation through timeCode1
Safe-FinRL: A Low Bias and Variance Deep Reinforcement Learning Implementation for High-Freq Stock Trading—0
Contrastive Learning for Unsupervised Domain Adaptation of Time SeriesCode1
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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