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 64016450 of 6748 papers

TitleStatusHype
Disk storage management for LHCb based on Data Popularity estimator0
Learning dynamic Boltzmann machines with spike-timing dependent plasticity0
Theoretical Analysis of the Optimal Free Responses of Graph-Based SFA for the Design of Training Graphs0
High-dimensional Time Series Prediction with Missing Values0
Optimal Copula Transport for Clustering Multivariate Time Series0
Quadratic Hawkes processes for financial prices0
Computational Intelligence Challenges and Applications on Large-Scale Astronomical Time Series Databases0
Spatially Encoding Temporal Correlations to Classify Temporal Data Using Convolutional Neural Networks0
Sparsity-based Correction of Exponential Artifacts0
Deep Temporal Sigmoid Belief Networks for Sequence ModelingCode0
A sequential approach to calibrate ecosystem models with multiple time series data0
Production Function of the Mining Sector of Iran0
Measuring multiscaling in financial time-series0
Joint multifractal analysis based on the partition function approach: Analytical analysis, numerical simulation and empirical application0
Impact of noise on a dynamical system: prediction and uncertainties from a swarm-optimized neural network0
A proposal of a methodological framework with experimental guidelines to investigate clustering stability on financial time series0
Regional and temporal characteristics of bovine tuberculosis of cattle in Great Britain0
Forecasting Method for Grouped Time Series with the Use of k-Means Algorithm0
Learning the Number of Autoregressive Mixtures in Time Series Using the Gap Statistics0
Discovering Causal Relations in Textual Instructions0
Reading Documents for Bayesian Online Change Point Detection0
Modeling Tweet Arrival Times using Log-Gaussian Cox Processes0
Squibs: Evaluation Methods for Statistically Dependent Text0
Online Supervised Subspace Tracking0
Forecasting Exchange Rates Using Time Series Analysis: The sample of the currency of Kazakhstan0
Recurrent Neural Network Based Modeling of Gene Regulatory Network Using Bat Algorithm0
Duration and Interval Hidden Markov Model for Sequential Data Analysis0
The (in)visible hand in the Libor market: an Information Theory approach0
Time Series Clustering via Community Detection in NetworksCode0
Fuzzy Longest Common Subsequence Matching With FCM Using R0
Bridging AIC and BIC: a new criterion for autoregression0
Time-series modeling with undecimated fully convolutional neural networks0
Quantitative evaluation of the performance of discrete-time reservoir computers in the forecasting, filtering, and reconstruction of stochastic stationary signals0
Forecasting Leading Death Causes in Australia using Extended CreditRisk+0
Modeling Website Workload Using Neural Networks0
Evaluation of Spectral Learning for the Identification of Hidden Markov Models0
Chaotic Neuronal Oscillations in Spontaneous Cortical-Subcortical Networks0
Multi-scaling of wholesale electricity prices0
AMP: a new time-frequency feature extraction method for intermittent time-series data0
Quantile Correlations: Uncovering temporal dependencies in financial time series0
Semi-parametric time series modelling with autocopulas0
Recursive Sparse Point Process Regression with Application to Spectrotemporal Receptive Field Plasticity Analysis0
Ensemble of Hankel Matrices for Face Emotion Recognition0
Quantum Gates and Quantum Circuits of Stock Portfolio0
Learning Leading Indicators for Time Series Predictions0
Anomaly Detection and Removal Using Non-Stationary Gaussian Processes0
Ranking election issues through the lens of social media0
Storylines for structuring massive streams of news0
A Frame of Mind: Using Statistical Models for Detection of Framing and Agenda Setting Campaigns0
Impact of non-stationarity on estimating and modeling empirical copulas of daily stock returnsCode0
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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