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 5976–6000 of 6748 papers

TitleStatusHype
Financial Series Prediction: Comparison Between Precision of Time Series Models and Machine Learning Methods—0
Unsupervised real-time anomaly detection for streaming dataCode0
imputeTS: Time Series Missing Value Imputation in RCode0
Integer Echo State Networks: Efficient Reservoir Computing for Digital Hardware—0
Krylov Subspace Recycling for Fast Iterative Least-Squares in Machine Learning—0
Large Linear Multi-output Gaussian Process LearningCode0
Accelerating Neural Architecture Search using Performance PredictionCode0
Test Models for Statistical Inference: Two-Dimensional Reaction Systems Displaying Limit Cycle Bifurcations and Bistability—0
Direct Mapping Hidden Excited State Interaction Patterns from ab initio Dynamics and Its Implications on Force Field Development—0
Automatic Response Assessment in Regions of Language Cortex in Epilepsy Patients Using ECoG-based Functional Mapping and Machine Learning—0
Identifying stochastic oscillations in single-cell live imaging time series using Gaussian processesCode0
Neural Decomposition of Time-Series Data for Effective Generalization—0
Sequence Summarization Using Order-constrained Kernelized Feature Subspaces—0
Modeling The Intensity Function Of Point Process Via Recurrent Neural NetworksCode0
Stochastic Sequential Neural Networks with Structured Inference—0
Non-Stationary Spectral KernelsCode0
Techniques for visualizing LSTMs applied to electrocardiograms—0
Learning the Morphology of Brain Signals Using Alpha-Stable Convolutional Sparse Coding—0
Machine learning modeling for time series problem: Predicting flight ticket pricesCode0
Prediction of Sea Surface Temperature using Long Short-Term Memory—0
Practical Processing of Mobile Sensor Data for Continual Deep Learning Predictions—0
Multiobjective Programming for Type-2 Hierarchical Fuzzy Inference TreesCode0
Ensemble of heterogeneous flexible neural trees using multiobjective genetic programmingCode0
A Long Short-Term Memory Recurrent Neural Network Framework for Network Traffic Matrix Prediction—0
Optimal Warping Paths are unique for almost every Pair of Time Series—0
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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