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 4101–4150 of 6748 papers

TitleStatusHype
Uncertainty Modelling in Risk-averse Supply Chain Systems Using Multi-objective Pareto Optimization—0
Correlation-aware Unsupervised Change-point Detection via Graph Neural NetworksCode1
Explicit Domain Adaptation with Loosely Coupled Samples—0
A Graph-constrained Changepoint Detection Approach for ECG Segmentation—0
Sensor selection on graphs via data-driven node sub-sampling in network time series—0
Rotated spectral principal component analysis (rsPCA) for identifying dynamical modes of variability in climate systems—0
Improving the Decision-Making Process of Self-Adaptive Systems by Accounting for Tactic Volatility—0
How to find a unicorn: a novel model-free, unsupervised anomaly detection method for time seriesCode1
Applications of shapelet transform to time series classification of earthquake, wind and wave data—0
Memory and forecasting capacities of nonlinear recurrent networks—0
Pattern-based Long Short-term Memory for Mid-term Electrical Load Forecasting—0
A New Metric for Lumpy and Intermittent Demand Forecasts: Stock-keeping-oriented Prediction Error Costs—0
MatchboxNet: 1D Time-Channel Separable Convolutional Neural Network Architecture for Speech Commands Recognition—0
Structural clustering of volatility regimes for dynamic trading strategies—0
Deep Learning for Time Series Forecasting: Tutorial and Literature SurveyCode2
A Deep Learning Approach for Motion Forecasting Using 4D OCT Data—0
Network Anomaly Detection based on Tensor Decomposition—0
COVID-19 Time-series Prediction by Joint Dictionary Learning and Online NMFCode0
SoQal: Selective Oracle Questioning for Consistency Based Active Learning of Cardiac SignalsCode0
A Critical Overview of Privacy-Preserving Approaches for Collaborative Forecasting—0
A Benchmark Study on Time Series Clustering—0
Characters as Graphs: Recognizing Online Handwritten Chinese Characters via Spatial Graph Convolutional Network—0
Information flow networks of Chinese stock market sectors—0
How macroscopic laws describe complex dynamics: asymptomatic population and CoviD-19 spreading—0
Tree Echo State Autoencoders with GrammarsCode0
Time Series Data Augmentation for Neural Networks by Time Warping with a Discriminative TeacherCode1
Kernels for time series with irregularly-spaced multivariate observations—0
Predicting Online Item-choice Behavior: A Shape-restricted Regression Perspective—0
A Time Series Analysis-Based Stock Price Prediction Using Machine Learning and Deep Learning Models—0
Outlier detection at the parcel-level in wheat and rapeseed crops using multispectral and SAR time series—0
Predictability of Power Grid Frequency—0
Exploring time-series motifs through DTW-SOM—0
Transfer Learning with Graph Neural Networks for Short-Term Highway Traffic ForecastingCode1
Forecasting Multi-Dimensional Processes over Graphs—0
Coronavirus (COVID-19): ARIMA based time-series analysis to forecast near future—0
Rapidly evaluating lockdown strategies using spectral analysis: the cycles behind new daily COVID-19 cases and what happens after lockdown—0
Random thoughts about Complexity, Data and Models—0
Characterizing the memory capacity of transmon qubit reservoirs—0
Asset Pricing with General Transaction Costs: Theory and Numerics—0
Conditional-UNet: A Condition-aware Deep Model for Coherent Human Activity Recognition From Wearables—0
Hidden Markov Neural Networks—0
Contrastive Blind Denoising Autoencoder for Real-Time Denoising of Industrial IoT Sensor Data—0
Detecting Driver's Distraction using Long-term Recurrent Convolutional Network—0
Minority Oversampling for Imbalanced Time Series ClassificationCode0
Co-eye: A Multi-resolution Symbolic Representation to TimeSeries Diversified Ensemble Classification—0
The leverage effect and other stylized facts displayed by Bitcoin returns—0
A tale of two toolkits, report the third: on the usage and performance of HIVE-COTE v1.0—0
Hybrid Attention Networks for Flow and Pressure Forecasting in Water Distribution Systems—0
Clustering Time Series Data through Autoencoder-based Deep Learning Models—0
On Error Correction Neural Networks for Economic Forecasting—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