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 2576–2600 of 6748 papers

TitleStatusHype
Clustering Discrete-Valued Time Series—0
Ensemble Grammar Induction For Detecting Anomalies in Time Series—0
Fast Active Set Methods for Online Spike Inference from Calcium Imaging—0
Compressed Factorization: Fast and Accurate Low-Rank Factorization of Compressively-Sensed Data—0
Applying SVGD to Bayesian Neural Networks for Cyclical Time-Series Prediction and Inference—0
Fast and Consistent Learning of Hidden Markov Models by Incorporating Non-Consecutive Correlations—0
Clustering evolving data using kernel-based methods—0
Clustering Financial Time Series: How Long is Enough?—0
Fast and Scalable Distributed Deep Convolutional Autoencoder for fMRI Big Data Analytics—0
Fast and Simple Optimization for Poisson Likelihood Models—0
Fast Automatic Feature Selection for Multi-Period Sliding Window Aggregate in Time Series—0
Fast Convolutive Nonnegative Matrix Factorization Through Coordinate and Block Coordinate Updates—0
Fast CRDNN: Towards on Site Training of Mobile Construction Machines—0
Fast Distribution Grid Line Outage Identification with μPMU—0
A Novel Multi-Centroid Template Matching Algorithm and Its Application to Cough Detection—0
Clustering Interval-Censored Time-Series for Disease Phenotyping—0
Faster than LASER -- Towards Stream Reasoning with Deep Neural Networks—0
Adaptive Complementary Ensemble EMD and Energy-Frequency Spectra of Cryptocurrency Prices—0
From FATS to feets: Further improvements to an astronomical feature extraction tool based on machine learning—0
Fast Function to Function Regression—0
Approximate Collapsed Gibbs Clustering with Expectation Propagation—0
FastGRNN: A Fast, Accurate, Stable and Tiny Kilobyte Sized Gated Recurrent Neural Network—0
Fast Inference for Quantile Regression with Tens of Millions of Observations—0
Ensemble Forecasting of Monthly Electricity Demand using Pattern Similarity-based Methods—0
Ensemble Deep Learning on Time-Series Representation of Tweets for Rumor Detection in Social Media—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