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 1951–2000 of 6748 papers

TitleStatusHype
Discovering physical concepts with neural networksCode0
A Full Probabilistic Model for Yes/No Type Crowdsourcing in Multi-Class ClassificationCode0
Discovering patterns of online popularity from time seriesCode0
Discovering Subdimensional Motifs of Different Lengths in Large-Scale Multivariate Time SeriesCode0
Discretize-Optimize vs. Optimize-Discretize for Time-Series Regression and Continuous Normalizing FlowsCode0
Dilated Convolutional Neural Networks for Time Series ForecastingCode0
A Framework for Imbalanced Time-series ForecastingCode0
Unsupervised Scalable Representation Learning for Multivariate Time SeriesCode0
Bidirectional deep-readout echo state networksCode0
Detecting Regions of Maximal Divergence for Spatio-Temporal Anomaly DetectionCode0
Beyond Sparsity: Tree Regularization of Deep Models for InterpretabilityCode0
Using Machine Learning to generate an open-access cropland map from satellite images time series in the Indian Himalayan RegionCode0
Differentially Private Multivariate Time Series Forecasting of Aggregated Human Mobility With Deep Learning: Input or Gradient Perturbation?Code0
Discovering long term dependencies in noisy time series data using deep learningCode0
Dropout Feature Ranking for Deep Learning ModelsCode0
EgPDE-Net: Building Continuous Neural Networks for Time Series Prediction with Exogenous VariablesCode0
On the separation of shape and temporal patterns in time series -Application to signature authentication-Code0
Bayesian Learning from Sequential Data using Gaussian Processes with Signature CovariancesCode0
Beyond Predictions in Neural ODEs: Identification and Interventions—0
Beyond Just Vision: A Review on Self-Supervised Representation Learning on Multimodal and Temporal Data—0
Anomaly Attribution of Multivariate Time Series using Counterfactual Reasoning—0
Beyond Convolutions: A Novel Deep Learning Approach for Raw Seismic Data Ingestion—0
Better than DFA? A Bayesian Method for Estimating the Hurst Exponent in Behavioral Sciences—0
Anomalous volatility scaling in high frequency financial data—0
A Framework for Exploring Non-Linear Functional Connectivity and Causality in the Human Brain: Mutual Connectivity Analysis (MCA) of Resting-State Functional MRI with Convergent Cross-Mapping and Non-Metric Clustering—0
Benign Overfitting in Time Series Linear Models with Over-Parameterization—0
Benefits of Depth for Long-Term Memory of Recurrent Networks—0
ANN Model to Predict Stock Prices at Stock Exchange Markets—0
Benefit-aware Early Prediction of Health Outcomes on Multivariate EEG Time Series—0
An NLP-Assisted Bayesian Time Series Analysis for Prevalence of Twitter Cyberbullying During the COVID-19 Pandemic—0
A Framework for Evaluating the Impact of Food Security Scenarios—0
Benchmarking Twitter Sentiment Analysis Tools—0
An LLM-Powered Agent for Physiological Data Analysis: A Case Study on PPG-based Heart Rate Estimation—0
An L0-Norm Constrained Non-Negative Matrix Factorization Algorithm for the Simultaneous Disaggregation of Fixed and Shiftable Loads—0
A framework for anomaly detection using language modeling, and its applications to finance—0
Benchmarking Online Sequence-to-Sequence and Character-based Handwriting Recognition from IMU-Enhanced Pens—0
Benchmarking Multivariate Time Series Classification Algorithms—0
An Investigation of the Structural Characteristics of the Indian IT Sector and the Capital Goods Sector: An Application of the R Programming in Time Series Decomposition and Forecasting—0
Benchmarking Energy-Conserving Neural Networks for Learning Dynamics from Data—0
Benchmarking Deep Sequential Models on Volatility Predictions for Financial Time Series—0
An investigation of higher order moments of empirical financial data and the implications to risk—0
A Frame of Mind: Using Statistical Models for Detection of Framing and Agenda Setting Campaigns—0
Actionable Interpretation of Machine Learning Models for Sequential Data: Dementia-related Agitation Use Case—0
Benchmarking adversarial attacks and defenses for time-series data—0
An Introductory Study on Time Series Modeling and Forecasting—0
An Introduction to Animal Movement Modeling with Hidden Markov Models using Stan for Bayesian Inference—0
A Fourier Transform Approach for Automatic Detection of Oysters Spawning—0
Behavioural Analytics: Mathematics of the Mind—0
Behave-XAI: Deep Explainable Learning of Behavioral Representational Data—0
Differentially-Private Heat and Electricity Markets Coordination—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