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 5351–5375 of 6748 papers

TitleStatusHype
Comparing Temporal Graphs Using Dynamic Time WarpingCode0
Task Runtime Prediction in Scientific Workflows Using an Online Incremental Learning Approach—0
Spikebench: An open benchmark for spike train time-series classificationCode0
Real time expert system for anomaly detection of aerators based on computer vision technology and existing surveillance cameras—0
Discretizing Logged Interaction Data Biases Learning for Decision-Making—0
Mining Novel Multivariate Relationships in Time Series Data Using Correlation NetworksCode0
Concept-drifting Data Streams are Time Series; The Case for Continuous Adaptation—0
Deconvolutional Time Series Regression: A Technique for Modeling Temporally Diffuse EffectsCode1
Learning Deep Representations from Clinical Data for Chronic Kidney Disease—0
Robust multivariate and functional archetypal analysis with application to financial time series analysis—0
Caulking the Leakage Effect in MEEG Source Connectivity AnalysisCode0
Adversarial Domain Adaptation for Stable Brain-Machine Interfaces—0
HyperST-Net: Hypernetworks for Spatio-Temporal Forecasting—0
Unified recurrent network for many feature types—0
A NOVEL VARIATIONAL FAMILY FOR HIDDEN NON-LINEAR MARKOV MODELS—0
Exploring the interpretability of LSTM neural networks over multi-variable data—0
A Short Survey of Topological Data Analysis in Time Series and Systems Analysis—0
Using Autoencoders To Learn Interesting Features For Detecting Surveillance Aircraft—0
Dataset: Rare Event Classification in Multivariate Time SeriesCode0
Supervised Nonnegative Matrix Factorization to Predict ICU Mortality Risk—0
Multi-task Learning for Financial Forecasting—0
Temporal Relational Ranking for Stock PredictionCode0
Complex market dynamics in the light of random matrix theory—0
A Comparative Study: Adaptive Fuzzy Inference Systems for Energy Prediction in Urban Buildings—0
Unified recurrent neural network for many feature types—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