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 4801–4825 of 6748 papers

TitleStatusHype
Heterogeneous Relational Kernel Learning—0
A framework for anomaly detection using language modeling, and its applications to finance—0
Generic Tracking and Probabilistic Prediction Framework and Its Application in Autonomous Driving—0
Enhanced Cyber-Physical Security through Deep Learning Techniques—0
Griffon: Reasoning about Job Anomalies with Unlabeled Data in Cloud-based Platforms—0
Time series model selection with a meta-learning approach; evidence from a pool of forecasting algorithms—0
Quantile Convolutional Neural Networks for Value at Risk Forecasting—0
Data-driven model reduction, Wiener projections, and the Koopman-Mori-Zwanzig formalism—0
Spatio-temporal Manifold Learning for Human Motions via Long-horizon Modeling—0
Detecting Gas Vapor Leaks Using Uncalibrated Sensors—0
A Review of Changepoint Detection Models—0
Semi-supervised Sequence Modeling for Elastic Impedance InversionCode0
Comparing linear structure-based and data-driven latent spatial representations for sequence prediction—0
Independence Testing for Temporal Data—0
Understanding Cyber Athletes Behaviour Through a Smart Chair: CS:GO and Monolith Team ScenarioCode0
eSports Pro-Players Behavior During the Game Events: Statistical Analysis of Data Obtained Using the Smart ChairCode0
Locally Linear Embedding and fMRI feature selection in psychiatric classification—0
Chaotic Time Series Prediction using Spatio-Temporal RBF Neural Networks—0
Comprehensive Time-Series Regression Models Using GRETL -- U.S. GDP and Government Consumption Expenditures & Gross Investment from 1980 to 2013—0
N2D: (Not Too) Deep Clustering via Clustering the Local Manifold of an Autoencoded EmbeddingCode0
HOTVis: Higher-Order Time-Aware Visualisation of Dynamic Graphs—0
A Machine Learning Approach for Smartphone-based Sensing of Roads and Driving Style—0
Mixed pooling of seasonality for time series forecasting: An application to pallet transport data—0
Towards automated symptoms assessment in mental health—0
MEx: Multi-modal Exercises Dataset for Human Activity RecognitionCode0
Show:102550
← PrevPage 193 of 270Next →
All datasetsPhysioNet Challenge 2012Speech CommandsVentilator Pressure Prediction

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