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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 1976–2000 of 6748 papers

TitleStatusHype
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