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

Showing 55015550 of 6748 papers

TitleStatusHype
Provably Calibrated Regression Under Distribution Drift0
Proximity Sensing: Modeling and Understanding Noisy RSSI-BLE Signals and Other Mobile Sensor Data for Digital Contact Tracing0
PRRS Outbreak Prediction via Deep Switching Auto-Regressive Factorization Modeling0
PSA-GAN: Progressive Self Attention GANs for Synthetic Time Series0
PSEUDo: Interactive Pattern Search in Multivariate Time Series with Locality-Sensitive Hashing and Relevance Feedback0
PSF : Introduction to R Package for Pattern Sequence Based Forecasting Algorithm0
PSO-MISMO Modeling Strategy for Multi-Step-Ahead Time Series Prediction0
Psychometric Analysis and Coupling of Emotions Between State Bulletins and Twitter in India during COVID-19 Infodemic0
Public Transit Arrival Prediction: a Seq2Seq RNN Approach0
PyChEst: a Python package for the consistent retrospective estimation of distributional changes in piece-wise stationary time series0
Pyramid Recurrent Neural Networks for Multi-Scale Change-Point Detection0
QIXAI: A Quantum-Inspired Framework for Enhancing Classical and Quantum Model Transparency and Understanding0
Quadratic Advantage with Quantum Randomized Smoothing Applied to Time-Series Analysis0
Quadratic Hawkes processes for financial prices0
Deep Metric Learning Model for Imbalanced Fault Diagnosis0
Qualitative Assessment of Recurrent Human Motion0
Quant GANs: Deep Generation of Financial Time Series0
Quantification in-the-wild: data-sets and baselines0
Quantification of metabolic niche occupancy dynamics in a Baltic Sea bacterial community0
Quantifying Causes of Arctic Amplification via Deep Learning based Time-series Causal Inference0
Quantifying How Hateful Communities Radicalize Online Users0
Quantifying Long Range Dependence in Language and User Behavior to improve RNNs0
Quantifying Quality of Class-Conditional Generative Models in Time-Series Domain0
Quantifying Synchronization in a Biologically Inspired Neural Network0
Quantifying the Economic Impact of Extreme Shocks on Businesses using Human Mobility Data: a Bayesian Causal Inference Approach0
Quantifying the Effects of COVID-19 on Restaurant Reviews0
Quantifying Volatility Reduction in German Day-ahead Spot Market in the Period 2006 through 20160
Quantile Autoregression-based Non-causality Testing0
Quantile-based fuzzy clustering of multivariate time series in the frequency domain0
Quantile-based fuzzy C-means clustering of multivariate time series: Robust techniques0
Quantile Correlations: Uncovering temporal dependencies in financial time series0
Quantile LSTM: A Robust LSTM for Anomaly Detection In Time Series Data0
Quantitative Evaluation of Full-Scale Ship Maneuvering Characteristics During Berthing and Unberthing0
Quantitative evaluation of the performance of discrete-time reservoir computers in the forecasting, filtering, and reconstruction of stochastic stationary signals0
Quantum Bohmian Inspired Potential to Model Non-Gaussian Events and the Application in Financial Markets0
Quantum Gates and Quantum Circuits of Stock Portfolio0
Quantum Persistent Homology for Time Series0
Quantum Quantile Mechanics: Solving Stochastic Differential Equations for Generating Time-Series0
Quasi-steady uptake and bacterial community assembly in a mathematical model of soil-phosphorus mobility0
A Query-Response Causal Analysis of Reaction Events in Biochemical Reaction Networks0
Quick and Easy Time Series Generation with Established Image-based GANs0
Quickest Detection of COVID-19 Pandemic Onset0
Quick Line Outage Identification in Urban Distribution Grids via Smart Meters0
Quick, Stat!: A Statistical Analysis of the Quick, Draw! Dataset0
R2N2: Residual Recurrent Neural Networks for Multivariate Time Series Forecasting0
Rademacher complexity of stationary sequences0
Random cohort effects and age groups dependency structure for mortality modelling and forecasting: Mixed-effects time-series model approach0
Random Feature Approximation for Online Nonlinear Graph Topology Identification0
Random Fragments Classification of Microbial Marker Clades with Multi-class SVM and N-Best Algorithm0
Randomized kernels for large scale Earth observation applications0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1naive classifierF187.47Unverified
2GRU-D - APC (n = 1)F127.3Unverified
3GRU-APC (n = 1)F125.7Unverified
4GRU-DF122.5Unverified
5GRUF122.3Unverified
6GRU-SimpleF122.2Unverified
7GRU-MeanF122.1Unverified
#ModelMetricClaimedVerifiedStatus
1SepTr% Test Accuracy98.51Unverified
2ViT% Test Accuracy98.11Unverified
3FlexTCN-4% Test Accuracy97.73Unverified
4MatchboxNet% Test Accuracy97.4Unverified
5CKCNN (100k)% Test Accuracy95.27Unverified
6FlexTCN-6% Test Accuracy (Raw Data)91.73Unverified
#ModelMetricClaimedVerifiedStatus
1ResBiLSTMMAE0.13Unverified