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 1151–1175 of 6748 papers

TitleStatusHype
Near Optimal Heteroscedastic Regression with Symbiotic Learning—0
Characterizing the Emotion Carriers of COVID-19 Misinformation and Their Impact on Vaccination Outcomes in India and the United States—0
Deep learning-based deconvolution for interferometric radio transient reconstructionCode0
An Error Correction Mid-term Electricity Load Forecasting Model Based on Seasonal Decomposition—0
Deep Learning for Energy Time-Series Analysis and Forecasting—0
BrainNet: Epileptic Wave Detection from SEEG with Hierarchical Graph Diffusion Learning—0
Improving Time Series Encoding with Noise-Aware Self-Supervised Learning and an Efficient EncoderCode0
Probabilistic Unrolling: Scalable, Inverse-Free Maximum Likelihood Estimation for Latent Gaussian Models—0
Switching Autoregressive Low-rank Tensor ModelsCode0
An OPC UA-based industrial Big Data architecture—0
Evaluating generation of chaotic time series by convolutional generative adversarial networksCode0
SAMoSSA: Multivariate Singular Spectrum Analysis with Stochastic Autoregressive Noise—0
Sliding Window Sum Algorithms for Deep Neural Networks—0
Bias, Consistency, and Partisanship in U.S. Asylum Cases: A Machine Learning Analysis of Extraneous Factors in Immigration Court Decisions—0
Comfort Foods and Community Connectedness: Investigating Diet Change during COVID-19 Using YouTube Videos on Twitter—0
Predicting Unplanned Readmissions in the Intensive Care Unit: A Multimodality Evaluation—0
Understand Waiting Time in Transaction Fee Mechanism: An Interdisciplinary PerspectiveCode0
Ordinal time series analysis with the R package otsfeatures—0
Non-destructive Fault Diagnosis of Electronic Interconnects by Learning Signal Patterns of Reflection Coefficient in the Frequency Domain—0
Filling out the missing gaps: Time Series Imputation with Semi-Supervised Learning—0
The short- and long-term determinants of fertility in Uruguay—0
Style Miner: Find Significant and Stable Explanatory Factors in Time Series with Constrained Reinforcement Learning—0
Forecasting COVID-19 Infections in Gulf Cooperation Council (GCC) Countries using Machine Learning—0
Deep incremental learning models for financial temporal tabular datasets with distribution shifts—0
Delay-SDE-net: A deep learning approach for time series modelling with memory and uncertainty estimatesCode0
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All datasetsPhysioNet Challenge 2012Speech CommandsVentilator Pressure Prediction

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