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 1001–1050 of 6748 papers

TitleStatusHype
A Formally Robust Time Series Distance Metric—0
Behavioural Analytics: Mathematics of the Mind—0
A dynamic conditional approach to portfolio weights forecasting—0
An Introduction to Animal Movement Modeling with Hidden Markov Models using Stan for Bayesian Inference—0
Benchmarking adversarial attacks and defenses for time-series data—0
An Experimental Evaluation of Nearest Neighbour Time Series Classification—0
A consistent deterministic regression tree for non-parametric prediction of time series—0
Chaotic Variational Auto encoder-based Adversarial Machine Learning—0
Benchmarking Multivariate Time Series Classification Algorithms—0
Benchmarking Online Sequence-to-Sequence and Character-based Handwriting Recognition from IMU-Enhanced Pens—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 Twitter Sentiment Analysis Tools—0
An LLM-Powered Agent for Physiological Data Analysis: A Case Study on PPG-based Heart Rate Estimation—0
Characterization of causal ancestral graphs for time series with latent confounders—0
Benefit-aware Early Prediction of Health Outcomes on Multivariate EEG Time Series—0
Benefits of Depth for Long-Term Memory of Recurrent Networks—0
Benign Overfitting in Time Series Linear Models with Over-Parameterization—0
Better than DFA? A Bayesian Method for Estimating the Hurst Exponent in Behavioral Sciences—0
Beyond Convolutions: A Novel Deep Learning Approach for Raw Seismic Data Ingestion—0
Beyond Just Vision: A Review on Self-Supervised Representation Learning on Multimodal and Temporal Data—0
Beyond Predictions in Neural ODEs: Identification and Interventions—0
A Wavelet-CNN-LSTM Model for Tailings Pond Risk Prediction—0
A Wavelet, AR and SVM based hybrid method for short-term wind speed prediction—0
An Expectation-Based Network Scan Statistic for a COVID-19 Early Warning System—0
A wavelet analysis of inter-dependence, contagion and long memory among global equity markets—0
A Wave is Worth 100 Words: Investigating Cross-Domain Transferability in Time Series—0
An Examination of Wearable Sensors and Video Data Capture for Human Exercise Classification—0
A Dynamic Bayesian Model for Interpretable Decompositions of Market Behaviour—0
A walk through of time series analysis on quantum computers—0
A volumetric change detection framework using UAV oblique photogrammetry - A case study of ultra-high-resolution monitoring of progressive building collapse—0
Adversarial Unsupervised Representation Learning for Activity Time-Series—0
A Visual Analytics Framework for Reviewing Multivariate Time-Series Data with Dimensionality Reduction—0
A Visibility Graph Averaging Aggregation Operator—0
A New Unified Deep Learning Approach with Decomposition-Reconstruction-Ensemble Framework for Time Series Forecasting—0
A conditional likelihood is required to estimate the selection coefficient in ancient DNA—0
A Benchmark Study on Time Series Clustering—0
Characterization of electric consumers through an automated clustering pipeline—0
A Video Recognition Method by using Adaptive Structural Learning of Long Short Term Memory based Deep Belief Network—0
A New State-of-the-Art Transformers-Based Load Forecaster on the Smart Grid Domain—0
Chaos in Fractionally Integrated Generalized Autoregressive Conditional Heteroskedastic Processes—0
A Variational Inference Approach to Inverse Problems with Gamma Hyperpriors—0
A New Metric for Lumpy and Intermittent Demand Forecasts: Stock-keeping-oriented Prediction Error Costs—0
Chaos may enhance expressivity in cerebellar granular layer—0
A Variational Autoencoder for Probabilistic Non-Negative Matrix Factorisation—0
Changes to the extreme and erratic behaviour of cryptocurrencies during COVID-19—0
A new measure between sets of probability distributions with applications to erratic financial behavior—0
Autowarp: Learning a Warping Distance from Unlabeled Time Series Using Sequence Autoencoders—0
AutoTS: Automatic Time Series Forecasting Model Design Based on Two-Stage Pruning—0
ABBA: Adaptive Brownian bridge-based symbolic aggregation of time series—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