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

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Showing 4251–4300 of 6748 papers

TitleStatusHype
Privacy-Aware Time-Series Data Sharing with Deep Reinforcement Learning—0
Optimally adaptive Bayesian spectral density estimation for stationary and nonstationary processes—0
Forecasting Sequential Data using Consistent Koopman AutoencodersCode1
Adaptive exponential power distribution with moving estimator for nonstationary time series—0
Pattern Similarity-based Machine Learning Methods for Mid-term Load Forecasting: A Comparative Study—0
Learning to Generate Time Series Conditioned Graphs with Generative Adversarial Nets—0
CRATOS: Cognition of Reliable Algorithm for Time-series Optimal Solution—0
The statistical physics of discovering exogenous and endogenous factors in a chain of events—0
Variational inference formulation for a model-free simulation of a dynamical system with unknown parameters by a recurrent neural network—0
Uncertainty-Aware Variational-Recurrent Imputation Network for Clinical Time SeriesCode0
GANs with Conditional Independence Graphs: On Subadditivity of Probability Divergences—0
Identity Recognition in Intelligent Cars with Behavioral Data and LSTM-ResNet Classifier—0
Dimensionality reduction to maximize prediction generalization capabilityCode1
1D CNN Based Network Intrusion Detection with Normalization on Imbalanced Data—0
Online Hierarchical Forecasting for Power Consumption Data—0
Forecasting Models for Daily Natural Gas Consumption Considering Periodic Variations and Demand Segregation—0
A Time-dependent SIR model for COVID-19 with Undetectable Infected PersonsCode1
DROCC: Deep Robust One-Class Classification—0
Wind Speed Prediction using Deep Ensemble Learning with a Jet-like Architecture—0
Complexity Measures and Features for Times Series classification—0
Time Series Data Augmentation for Deep Learning: A Survey—0
Prediction of adverse events in Afghanistan: regression analysis of time series data grouped not by geographic dependencies—0
How Much Can A Retailer Sell? Sales Forecasting on Tmall—0
A Kernel to Exploit Informative Missingness in Multivariate Time Series from EHRs—0
Evaluation of Temporal Complexity Reduction Techniques Applied to Storage Expansion Planning in Power System Models—0
Geometric Fusion via Joint Delay Embeddings—0
Block Hankel Tensor ARIMA for Multiple Short Time Series ForecastingCode0
Multivariate time-series modeling with generative neural networks—0
Non-Volatile Memory Array Based Quantization- and Noise-Resilient LSTM Neural Networks—0
Adaptive Transmit Waveform Design using Multi-Tone Sinusoidal Frequency Modulation—0
Modeling Continuous Stochastic Processes with Dynamic Normalizing FlowsCode1
Omni-Scale CNNs: a simple and effective kernel size configuration for time series classificationCode1
Variational Hyper RNN for Sequence Modeling—0
Predicting Coronal Mass Ejections Using SDO/HMI Vector Magnetic Data Products and Recurrent Neural NetworksCode0
A New Unified Deep Learning Approach with Decomposition-Reconstruction-Ensemble Framework for Time Series Forecasting—0
Longitudinal Support Vector Machines for High Dimensional Time Series—0
Human Activity Recognition using Multi-Head CNN followed by LSTMCode0
Causal structure learning from time series: Large regression coefficients may predict causal links better in practice than small p-valuesCode1
RobustTAD: Robust Time Series Anomaly Detection via Decomposition and Convolutional Neural Networks—0
RobustPeriod: Time-Frequency Mining for Robust Multiple Periodicity DetectionCode1
Forecasting Realized Volatility Matrix With Copula-Based Models—0
SummerTime: Variable-length Time SeriesSummarization with Applications to PhysicalActivity Analysis—0
Autonomous Discovery of Unknown Reaction Pathways from Data by Chemical Reaction Neural NetworkCode1
Forecasting Foreign Exchange Rate: A Multivariate Comparative Analysis between Traditional Econometric, Contemporary Machine Learning & Deep Learning TechniquesCode1
Network Clustering Via Kernel-ARMA Modeling and the Grassmannian The Brain-Network Case—0
Conditional Mutual information-based Contrastive Loss for Financial Time Series Forecasting—0
Dynamic Graph Learning based on Graph Laplacian—0
Controlled time series generation for automotive software-in-the-loop testing using GANs—0
Multivariate Probabilistic Time Series Forecasting via Conditioned Normalizing FlowsCode2
Deep reconstruction of strange attractors from time seriesCode1
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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