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 4701–4725 of 6748 papers

TitleStatusHype
Explicit-Duration Markov Switching Models—0
A tale of two toolkits, report the first: benchmarking time series classification algorithms for correctness and efficiency—0
Functional Annotation of Human Cognitive States using Graph Convolution Networks—0
Asset correlation estimation for inhomogeneous exposure pools—0
Multi-Year Vector Dynamic Time Warping Based Crop Mapping—0
InceptionTime: Finding AlexNet for Time Series ClassificationCode1
LSTM-MSNet: Leveraging Forecasts on Sets of Related Time Series with Multiple Seasonal PatternsCode0
Photometric light curves classification with machine learning—0
Scalable Structure Learning of Continuous-Time Bayesian Networks from Incomplete Data—0
Building Calibrated Deep Models via Uncertainty Matching with Auxiliary Interval PredictorsCode1
Super ensemble learning for daily streamflow forecasting: Large-scale demonstration and comparison with multiple machine learning algorithms—0
Real Time Trajectory Prediction Using Deep Conditional Generative ModelsCode0
Estimating Granger Causality with Unobserved Confounders via Deep Latent-Variable Recurrent Neural Network—0
Feature-Set-Engineering for Detecting Freezing of Gait in Parkinson's Disease using Deep Recurrent Neural Networks—0
Recovery of Future Data via Convolution Nuclear Norm MinimizationCode0
Automated Polysomnography Analysis for Detection of Non-Apneic and Non-Hypopneic Arousals using Feature Engineering and a Bidirectional LSTM Network—0
Blackbox Attacks on Reinforcement Learning Agents Using Approximated Temporal Information—0
Table-to-Text Generation with Effective Hierarchical Encoder on Three Dimensions (Row, Column and Time)Code0
State Drug Policy Effectiveness: Comparative Policy Analysis of Drug Overdose Mortality—0
Inferring species interactions using Granger causality and convergent cross mappingCode0
CalBehav: A Machine Learning based Personalized Calendar Behavioral Model using Time-Series Smartphone Data—0
Reusing Convolutional Activations from Frame to Frame to Speed up Training and InferenceCode0
Recurrent Neural Networks for Time Series Forecasting: Current Status and Future DirectionsCode0
Adaptive Anomaly Detection in Chaotic Time Series with a Spatially Aware Echo State NetworkCode0
Multilingual Dynamic Topic Model—0
Show:102550
← PrevPage 189 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