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 1176–1200 of 6748 papers

TitleStatusHype
Delay-SDE-net: A deep learning approach for time series modelling with memory and uncertainty estimatesCode0
Deep incremental learning models for financial temporal tabular datasets with distribution shifts—0
Sinkhorn-Flow: Predicting Probability Mass Flow in Dynamical Systems Using Optimal Transport—0
Hybrid Variational Autoencoder for Time Series Forecasting—0
Mobile Mapping Mesh Change Detection and Update—0
Comparing statistical and machine learning methods for time series forecasting in data-driven logistics -- A simulation study—0
Towards Unsupervised Learning based Denoising of Cyber Physical System Data to Mitigate Security Concerns—0
A Fourier Transform Approach for Automatic Detection of Oysters Spawning—0
DOMINO: Visual Causal Reasoning with Time-Dependent Phenomena—0
Informative regularization for a multi-layer perceptron RR Lyrae classifier under data shiftCode0
Explainable AI for Time Series via Virtual Inspection Layers—0
Accurate Prediction of Global Mean Temperature through Data Transformation Techniques—0
A Novel Method Combines Moving Fronts, Data Decomposition and Deep Learning to Forecast Intricate Time Series—0
On Neural Architectures for Deep Learning-based Source Separation of Co-Channel OFDM SignalsCode0
Machine Learning Enhanced Hankel Dynamic-Mode Decomposition—0
Sliced-Wasserstein on Symmetric Positive Definite Matrices for M/EEG SignalsCode0
Local-Global Methods for Generalised Solar Irradiance Forecasting—0
On the Soundness of XAI in Prognostics and Health Management (PHM)Code0
Multi-task Meta Label Correction for Time Series PredictionCode0
Learning Representation for Anomaly Detection of Vehicle Trajectories—0
Efficient Certified Training and Robustness Verification of Neural ODEsCode0
Depression Diagnosis and Drug Response Prediction via Recurrent Neural Networks and Transformers Utilizing EEG Signals—0
Distributional Vector Autoregression: Eliciting Macro and Financial Dependence—0
Self-contained Beta-with-Spikes Approximation for Inference Under a Wright-Fisher Model—0
Multimodal Multi-User Surface Recognition with the Kernel Two-Sample TestCode0
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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