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

Showing 51515200 of 6748 papers

TitleStatusHype
On Clustering Time Series Using Euclidean Distance and Pearson Correlation0
On Computational Complexity Reduction Methods for Kalman Filter Extensions0
On Consistency and Asymptotic Normality of Least Absolute Deviation Estimators for 2-dimensional Sinusoidal Model0
On Designing Data Models for Energy Feature Stores0
On Disentanglement in Gaussian Process Variational Autoencoders0
On Early-stage Debunking Rumors on Twitter: Leveraging the Wisdom of Weak Learners0
One-class Collective Anomaly Detection based on Long Short-Term Memory Recurrent Neural Networks0
One-dimensional Deep Image Prior for Time Series Inverse Problems0
One model is not enough: heterogeneity in cryptocurrencies' multifractal profiles0
ONE-NAS: An Online NeuroEvolution based Neural Architecture Search for Time Series Forecasting0
On Error Correction Neural Networks for Economic Forecasting0
One-shot Learning for iEEG Seizure Detection Using End-to-end Binary Operations: Local Binary Patterns with Hyperdimensional Computing0
One-Step or Two-Step Optimization and the Overfitting Phenomenon: A Case Study on Time Series Classification0
On Estimation and Inference of Large Approximate Dynamic Factor Models via the Principal Component Analysis0
On Improving Deep Reinforcement Learning for POMDPs0
On LASSO for High Dimensional Predictive Regression0
Online Advertising Revenue Forecasting: An Interpretable Deep Learning Approach0
Online Anomaly Detection with Sparse Gaussian Processes0
Online change-point detection with kernels0
Online Collection and Forecasting of Resource Utilization in Large-Scale Distributed Systems0
Online Debiasing for Adaptively Collected High-dimensional Data with Applications to Time Series Analysis0
Online deforestation detection0
Online Detection of Changes in Moment-Based Projections: When to Retrain Deep Learners or Update Portfolios?0
Online detection of failures generated by storage simulator0
Online estimation methods for irregular autoregressive models0
Online Estimation of Multiple Dynamic Graphs in Pattern Sequences0
Online Evolutionary Neural Architecture Search for Multivariate Non-Stationary Time Series Forecasting0
Online false discovery rate control for anomaly detection in time series0
Online Forecasting Matrix Factorization0
Online Graph Topology Learning from Matrix-valued Time Series0
Online Hierarchical Forecasting for Power Consumption Data0
Online Joint Topology Identification and Signal Estimation from Streams with Missing Data0
Online Learning Algorithm for Time Series Forecasting Suitable for Low Cost Wireless Sensor Networks Nodes0
Online learning of both state and dynamics using ensemble Kalman filters0
Online Learning of the Kalman Filter with Logarithmic Regret0
Online learning of windmill time series using Long Short-term Cognitive Networks0
Online Learning with Predictable Sequences0
Online Learning with Radial Basis Function Networks0
Online Multi-horizon Transaction Metric Estimation with Multi-modal Learning in Payment Networks0
Online Non-linear Topology Identification from Graph-connected Time Series0
Online Real-time Learning of Dynamical Systems from Noisy Streaming Data: A Koopman Operator Approach0
OnlineSTL: Scaling Time Series Decomposition by 100x0
On-line Summarization of Time-series Documents using a Graph-based Algorithm0
Online Supervised Subspace Tracking0
Online Time Series Anomaly Detection with State Space Gaussian Processes0
Online Training of an Opto-Electronic Reservoir Computer Applied to Real-Time Channel Equalisation0
On Lyapunov exponents and adversarial perturbation0
On Merging Feature Engineering and Deep Learning for Diagnosis, Risk-Prediction and Age Estimation Based on the 12-Lead ECG0
On Multivariate Financial Time Series Classification0
On Multivariate Singular Spectrum Analysis and its Variants0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1naive classifierF187.47Unverified
2GRU-D - APC (n = 1)F127.3Unverified
3GRU-APC (n = 1)F125.7Unverified
4GRU-DF122.5Unverified
5GRUF122.3Unverified
6GRU-SimpleF122.2Unverified
7GRU-MeanF122.1Unverified
#ModelMetricClaimedVerifiedStatus
1SepTr% Test Accuracy98.51Unverified
2ViT% Test Accuracy98.11Unverified
3FlexTCN-4% Test Accuracy97.73Unverified
4MatchboxNet% Test Accuracy97.4Unverified
5CKCNN (100k)% Test Accuracy95.27Unverified
6FlexTCN-6% Test Accuracy (Raw Data)91.73Unverified
#ModelMetricClaimedVerifiedStatus
1ResBiLSTMMAE0.13Unverified