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 951–1000 of 6748 papers

TitleStatusHype
A fast noise filtering algorithm for time series prediction using recurrent neural networks—0
Animal behavior classification via deep learning on embedded systems—0
Animal Behavior Classification via Accelerometry Data and Recurrent Neural Networks—0
A Fast Evidential Approach for Stock Forecasting—0
A Consistent Method for Learning OOMs from Asymptotically Stationary Time Series Data Containing Missing Values—0
A fast algorithm for complex discord searches in time series: HOT SAX Time—0
Independence Testing for Temporal Data—0
ANFIS-based prediction of power generation for combined cycle power plant—0
1D CNN Based Network Intrusion Detection with Normalization on Imbalanced Data—0
Forecasting Drought Using Multilayer Perceptron Artificial Neural Network Model—0
Backpropagation on Dynamical Networks—0
Backpropagation-Free Learning Method for Correlated Fuzzy Neural Networks—0
Backdoor Attacks against Transfer Learning with Pre-trained Deep Learning Models—0
The leverage effect and other stylized facts displayed by Bitcoin returns—0
Bag of Recurrence Patterns Representation for Time-Series Classification—0
Balancing Suspense and Surprise: Timely Decision Making with Endogenous Information Acquisition—0
Bandwidth-efficient distributed neural network architectures with application to body sensor networks—0
Basic Filters for Convolutional Neural Networks Applied to Music: Training or Design?—0
Impulse data models for the inverse problem of electrocardiography—0
Bayesian Alignments of Warped Multi-Output Gaussian Processes—0
Bayesian autoregressive spectral estimation—0
Bayesian Bilinear Neural Network for Predicting the Mid-price Dynamics in Limit-Order Book Markets—0
Bayesian Convolutional Deep Sets with Task-Dependent Stationary Prior—0
Bayesian Filtering for Multi-period Mean-Variance Portfolio Selection—0
Causal Inference via Kernel Deviance Measures—0
Causality and Correlations between BSE and NYSE indexes: A Janus Faced Relationship—0
Bayesian inference and superstatistics to describe long memory processes of financial time series—0
Bayesian Inference in High-Dimensional Time-Serieswith the Orthogonal Stochastic Linear Mixing Model—0
Bayesian inference of chaotic dynamics by merging data assimilation, machine learning and expectation-maximization—0
Bayesian inference of natural selection from allele frequency time series—0
Bayesian LSTMs in medicine—0
Bayesian multi--dipole localization and uncertainty quantification from simultaneous EEG and MEG recordings—0
Causal Mechanism Transfer Network for Time Series Domain Adaptation in Mechanical Systems—0
Estimation and Inference in High-Dimensional Panel Data Models with Interactive Fixed Effects—0
Bayesian nonparametric shared multi-sequence time series segmentation—0
Bayesian nonparametric sparse VAR models—0
Affine and Regional Dynamic Time Warpng—0
A Context Integrated Relational Spatio-Temporal Model for Demand and Supply Forecasting—0
Bayesian Online Change Point Detection for Baseline Shifts—0
Bayesian Optimisation for a Biologically Inspired Population Neural Network—0
Aedes-AI: Neural Network Models of Mosquito Abundance—0
Bayesian Realized-GARCH Models for Financial Tail Risk Forecasting Incorporating Two-sided Weibull Distribution—0
Bayesian Recurrent Framework for Missing Data Imputation and Prediction with Clinical Time Series—0
Bayesian Regression Approach for Building and Stacking Predictive Models in Time Series Analytics—0
AWT -- Clustering Meteorological Time Series Using an Aggregated Wavelet Tree—0
Bayesian Synthesis of Probabilistic Programs for Automatic Data Modeling—0
A Worrying Analysis of Probabilistic Time-series Models for Sales Forecasting—0
Bayesian Time Series Forecasting with Change Point and Anomaly Detection—0
An Explainer for Temporal Graph Neural Networks—0
Causal Inference for Time series Analysis: Problems, Methods and Evaluation—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