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
Deep Mixed Effect Model using Gaussian Processes: A Personalized and Reliable Prediction for HealthcareCode1
History Playground: A Tool for Discovering Temporal Trends in Massive Textual Corpora0
Hierarchical Attention-Based Recurrent Highway Networks for Time Series PredictionCode0
Quantifying the dynamics of topical fluctuations in languageCode0
Jerk-Aware Video Acceleration Magnification0
Deep Neural Models of Semantic Shift0
RiskFinder: A Sentence-level Risk Detector for Financial Reports0
Sea surface temperature prediction and reconstruction using patch-level neural network representations0
Root-cause Analysis for Time-series Anomalies via Spatiotemporal Graphical Modeling in Distributed Complex Systems0
Metric on Nonlinear Dynamical Systems with Perron-Frobenius OperatorsCode0
Predicting County Level Corn Yields Using Deep Long Short Term Memory Models0
Unsupervised detection of diachronic word sense evolution0
Currency exchange prediction using machine learning, genetic algorithms and technical analysis0
BRITS: Bidirectional Recurrent Imputation for Time SeriesCode0
Adversarial Constraint Learning for Structured PredictionCode0
Statistical properties and multifractality of Bitcoin0
Learning Nonlinear Brain Dynamics: van der Pol Meets LSTM0
Structure Learning from Time Series with False Discovery Control0
Multivariate Convolutional Sparse Coding for Electromagnetic Brain SignalsCode0
Dynamic Advisor-Based Ensemble (dynABE): Case study in stock trend prediction of critical metal companies0
Model Selection in Time Series Analysis: Using Information Criteria as an Alternative to Hypothesis Testing0
Optimal Transport for structured data with application on graphsCode2
Machine-learning inference of fluid variables from data using reservoir computing0
Approximate Newton-based statistical inference using only stochastic gradients0
Multi-Statistic Approximate Bayesian Computation with Multi-Armed Bandits0
Structured Bayesian Gaussian process latent variable model0
Nonlinear ICA Using Auxiliary Variables and Generalized Contrastive LearningCode0
NEWMA: a new method for scalable model-free online change-point detectionCode0
STS Classification with Dual-stream CNN0
DLBI: Deep learning guided Bayesian inference for structure reconstruction of super-resolution fluorescence microscopyCode0
On Attention Models for Human Activity Recognition0
Deep Generative Markov State ModelsCode0
Multitaper Spectral Estimation HDP-HMMs for EEG Sleep Inference0
Taxi demand forecasting: A HEDGE based tessellation strategy for improved accuracy0
Analyzing high-dimensional time-series data using kernel transfer operator eigenfunctions0
A Tempt to Unify Heterogeneous Driving Databases using Traffic Primitives0
Improved Predictive Models for Acute Kidney Injury with IDEAs: Intraoperative Data Embedded Analytics0
Robust and Scalable Models of Microbiome Dynamics0
Structural Breaks in Time Series0
Density Forecasts in Panel Data Models: A Semiparametric Bayesian Perspective0
Towards a universal neural network encoder for time series0
An Unsupervised Clustering-Based Short-Term Solar Forecasting Methodology Using Multi-Model Machine Learning Blending0
Foundations of Sequence-to-Sequence Modeling for Time Series0
Learning representations for multivariate time series with missing data using Temporal Kernelized Autoencoders0
Real-time regression analysis with deep convolutional neural networksCode0
30m resolution Global Annual Burned Area Mapping based on Landsat images and Google Earth Engine0
Dynamic and Static Topic Model for Analyzing Time-Series Document Collections0
Modeling Dengue Vector Population Using Remotely Sensed Data and Machine Learning0
Using Quantum Mechanics to Cluster Time Series0
An Evaluation of Classification and Outlier Detection Algorithms0
Show:102550
← PrevPage 111 of 135Next →

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