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 3176–3200 of 6748 papers

TitleStatusHype
Foundations of Sequence-to-Sequence Modeling for Time Series—0
Foundation Models for Time Series: A Survey—0
FormerTime: Hierarchical Multi-Scale Representations for Multivariate Time Series Classification—0
IIT-GAN: Irregular and Intermittent Time-series Synthesis with Generative Adversarial Networks—0
Image Embedding of PMU Data for Deep Learning towards Transient Disturbance Classification—0
Composite FORCE learning of chaotic echo state networks for time-series prediction—0
A review on outlier/anomaly detection in time series data—0
Forgery Attack Detection in Surveillance Video Streams Using Wi-Fi Channel State Information—0
Forestry digital twin with machine learning in Landsat 7 data—0
Composable Generative Models—0
IMG-NILM: A Deep learning NILM approach using energy heatmaps—0
I miss you babe: Analyzing Emotion Dynamics During COVID-19 Pandemic—0
Impact analysis of recovery cases due to COVID19 using LSTM deep learning model—0
Impact of Data Normalization on Deep Neural Network for Time Series Forecasting—0
Impact of noise on a dynamical system: prediction and uncertainties from a swarm-optimized neural network—0
Foreign exchange risk premia: from traditional to state-space analyses—0
Foreign Exchange Market Performance: Evidence from Bivariate Time Series Approach—0
Implications of Mortality Displacement for Effect Modification and Selection Bias—0
Complex-valued Gaussian Process Regression for Time Series Analysis—0
Importance attribution in neural networks by means of persistence landscapes of time series—0
Imposing Connectome-Derived Topology on an Echo State Network—0
A review on distance based time series classification—0
Improved Dynamic Time Warping (DTW) Approach for Online Signature Verification—0
Improved FRQI on superconducting processors and its restrictions in the NISQ era—0
A Method for Massively Parallel Analysis of Time Series—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