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 3651–3700 of 6748 papers

TitleStatusHype
4D Human Body Capture from Egocentric Video via 3D Scene Grounding—0
Early Detection of Thermoacoustic Instabilities in a Cryogenic Rocket Thrust Chamber using Combustion Noise Features and Machine Learning—0
Backpropagation-Free Learning Method for Correlated Fuzzy Neural Networks—0
Feature space approximation for kernel-based supervised learningCode0
Asymmetric excitation of left- and right-tail extreme events probed using a Hawkes model: application to financial returns—0
A Non-linear Function-on-Function Model for Regression with Time Series Data—0
Discovering Hidden Physics Behind Transport Dynamics—0
CASU2Net: Cascaded Unification Network by a Two-step Early Fusion for Fault Detection in Offshore Wind Turbines—0
Gaussian Processes for Traffic Speed Prediction at Different Aggregation Levels—0
RTFN: A Robust Temporal Feature Network for Time Series Classification—0
Deep Sequence Learning for Accurate Gestational Age Estimation from a \$25 Doppler Device—0
Analysis of Empirical Mode Decomposition-based Load and Renewable Time Series Forecasting—0
Scalable Hybrid Hidden Markov Model with Gaussian Process Emission for Sequential Time-series Observations—0
Marginalised Spectral Mixture Kernels with Nested Sampling—0
Time Series Data Imputation: A Survey on Deep Learning Approaches—0
Predictive maintenance on event logs: Application on an ATM fleet—0
Continuous Ant-Based Neural Topology Search—0
Central and Non-central Limit Theorems arising from the Scattering Transform and its Neural Activation Generalization—0
A Worrying Analysis of Probabilistic Time-series Models for Sales Forecasting—0
Quickest Detection of COVID-19 Pandemic Onset—0
Deep Directed Information-Based Learning for Privacy-Preserving Smart Meter Data Release—0
Combining Deep Transfer Learning with Signal-image Encoding for Multi-Modal Mental Wellbeing Classification—0
Two-Step Meta-Learning for Time-Series Forecasting Ensemble—0
Improved Grey System Models for Predicting Traffic Parameters—0
A Knowledge Distillation Ensemble Framework for Predicting Short and Long-term Hospitalisation Outcomes from Electronic Health Records DataCode0
Visual Time Series Forecasting: An Image-driven Approach—0
A Two-Way Transformed Factor Model for Matrix-Variate Time Series—0
Distributional uncertainty of the financial time series measured by G-expectation—0
Wavelet-based clustering for time-series trend detection—0
A Time-Frequency based Suspicious Activity Detection for Anti-Money Laundering—0
Distributed Online Learning with Multiple Kernels—0
Phenotyping Clusters of Patient Trajectories suffering from Chronic Complex Disease—0
Learning Sentinel-2 Spectral Dynamics for Long-Run Predictions Using Residual Neural Networks—0
Anonymizing Sensor Data on the Edge: A Representation Learning and Transformation Approach—0
Large-scale kernelized GRANGER causality to infer topology of directed graphs with applications to brain networks—0
Transfer learning of chaotic systems—0
Pix2Streams: Dynamic Hydrology Maps from Satellite-LiDAR Fusion—0
Discovering long term dependencies in noisy time series data using deep learningCode0
Determinantal Point Processes Implicitly Regularize Semi-parametric Regression Problems—0
Non-stationary Online Regression—0
Energy consumption forecasting using a stacked nonparametric Bayesian approach—0
Deep Neural Networks and Neuro-Fuzzy Networks for Intellectual Analysis of Economic Systems—0
Personality-Driven Gaze Animation with Conditional Generative Adversarial Networks—0
Pattern recognition in micro-trading behaviors before stock price jumps: A framework based on multivariate time series analysis—0
ATCN: Resource-Efficient Processing of Time Series on EdgeCode0
Forecasting and Analyzing the Military Expenditure of India Using Box-Jenkins ARIMA Model—0
Testing and Dating Structural Changes in Copula-based Dependence Measures—0
Applications of Online Nonnegative Matrix Factorization to Image and Time-Series Data—0
A Soft Computing Approach for Selecting and Combining Spectral Bands—0
Forecasting Emergency Department Capacity Constraints for COVID Isolation Beds—0
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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