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

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Showing 5801–5850 of 6748 papers

TitleStatusHype
Probabilistic AutoRegressive Neural Networks for Accurate Long-range ForecastingCode0
Visually Evaluating Generative Adversarial Networks Using Itself under Multivariate Time SeriesCode0
Non-iterative Calculation of Quasi-Dynamic Energy Flow in the Heat and Electricity Integrated Energy SystemsCode0
Data augmentation through multivariate scenario forecasting in Data Centers using Generative Adversarial NetworksCode0
Bridging Simplicity and Sophistication using GLinear: A Novel Architecture for Enhanced Time Series PredictionCode0
Identifying Exoplanets with Deep Learning. V. Improved Light Curve Classification for TESS Full Frame Image ObservationsCode0
Nonlinear ICA Using Auxiliary Variables and Generalized Contrastive LearningCode0
Integrating Attention Feedback into the Recurrent Neural NetworkCode0
Nonlinear Independent Component Analysis for Discrete-Time and Continuous-Time SignalsCode0
Identifying cross country skiing techniques using power meters in ski polesCode0
Recurrent Neural Networks for Time Series Forecasting: Current Status and Future DirectionsCode0
Recurrent Neural ProcessesCode0
Intelligence, physics and information -- the tradeoff between accuracy and simplicity in machine learningCode0
Identifying Causal Effects using Instrumental Time Series: Nuisance IV and Correcting for the PastCode0
Inter- and Intra-Series Embeddings Fusion Network for Epidemiological ForecastingCode0
Nonlinear methods to quantify Movement Variability in Human-Humanoid Interaction ActivitiesCode0
Distribution Agnostic Symbolic Representations for Time Series Dimensionality Reduction and Online Anomaly DetectionCode0
Interpolation-Prediction Networks for Irregularly Sampled Time SeriesCode0
Recurrent switching linear dynamical systemsCode0
Data augmentation on-the-fly and active learning in data stream classificationCode0
Nonlinear Time Series Classification Using Bispectrum-based Deep Convolutional Neural NetworksCode0
An Interpretable and Sparse Neural Network Model for Nonlinear Granger Causality DiscoveryCode0
Recursive classification of satellite imaging time-series: An application to land cover mappingCode0
Recursive deep learning framework for forecasting the decadal world economic outlookCode0
BreizhCrops: A Time Series Dataset for Crop Type MappingCode0
BrazilDAM: A Benchmark dataset for Tailings Dam DetectionCode0
Tripletformer for Probabilistic Interpolation of Irregularly sampled Time SeriesCode0
Identification of Abnormal States in Videos of Ants Undergoing Social Phase ChangeCode0
Times series averaging and denoising from a probabilistic perspective on time-elastic kernelsCode0
The effect of phased recurrent units in the classification of multiple catalogs of astronomical lightcurvesCode0
Hybrid Deep Neural Networks to Infer State Models of Black-Box SystemsCode0
Non-parametric Estimation of Stochastic Differential Equations with Sparse Gaussian ProcessesCode0
Recursive Tree Grammar AutoencodersCode0
DAMNETS: A Deep Autoregressive Model for Generating Markovian Network Time SeriesCode0
The effects of regularisation on RNN models for time series forecasting: Covid-19 as an exampleCode0
Human Activity Recognition using Multi-Head CNN followed by LSTMCode0
Homological Time Series Analysis of Sensor Signals from Power PlantsCode0
Highly Scalable and Provably Accurate Classification in Poincare BallsCode0
Boosting: Why You Can Use the HP FilterCode0
Reduced Order Probabilistic Emulation for Physics-Based Thermosphere ModelsCode0
Block-Structure Based Time-Series Models For Graph SequencesCode0
Block Hankel Tensor ARIMA for Multiple Short Time Series ForecastingCode0
Nonparametric Value-at-Risk via Sieve EstimationCode0
A Deep Learning Approach to Probabilistic Forecasting of WeatherCode0
Interpreting County Level COVID-19 Infection and Feature Sensitivity using Deep Learning Time Series ModelsCode0
SeqLink: A Robust Neural-ODE Architecture for Modelling Partially Observed Time SeriesCode0
Reforming the State-Based Forward Guidance through Wage Growth Rate Threshold: Evidence from FRB/US SimulationsCode0
Interpreting LSTM Prediction on Solar Flare Eruption with Time-series ClusteringCode0
High-dimensional regression with potential prior information on variable importanceCode0
High dimensional regression for regenerative time-series: an application to road traffic modelingCode0
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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