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 5226–5250 of 6748 papers

TitleStatusHype
A Comparison of LSTMs and Attention Mechanisms for Forecasting Financial Time Series—0
Video Trajectory Classification and Anomaly Detection Using Hybrid CNN-VAECode0
Unsupervised Anomaly Detection in Energy Time Series Data Using Variational Recurrent Autoencoders with Attention—0
Using Detailed Access Trajectories for Learning Behavior Analysis—0
Sequence Prediction using Spectral RNNsCode0
Impact of Data Normalization on Deep Neural Network for Time Series Forecasting—0
Combining Sentinel-1 and Sentinel-2 Time Series via RNN for object-based land cover classification—0
E-RNN: Design Optimization for Efficient Recurrent Neural Networks in FPGAs—0
Deep Air Quality Forecasting Using Hybrid Deep Learning Framework—0
Closed-form Inference and Prediction in Gaussian Process State-Space Models—0
Bitcoin Forecasting Using ARIMA and PROPHET—0
A Hybrid Distribution Feeder Long-Term Load Forecasting Method Based on Sequence Prediction—0
Applying Nature-Inspired Optimization Algorithms for Selecting Important Timestamps to Reduce Time Series Dimensionality—0
Fast Training Algorithms for Deep Convolutional Fuzzy Systems with Application to Stock Index Prediction—0
DOSED: a deep learning approach to detect multiple sleep micro-events in EEG signalCode0
seq2graph: Discovering Dynamic Dependencies from Multivariate Time Series with Multi-level Attention—0
Time Series Featurization via Topological Data Analysis—0
A novel health risk model based on intraday physical activity time series collected by smartphones—0
Anomaly detection with Wasserstein GAN—0
Time-Discounting Convolution for Event Sequences with Ambiguous Timestamps—0
RobustSTL: A Robust Seasonal-Trend Decomposition Algorithm for Long Time SeriesCode0
Estimation of multivariate asymmetric power GARCH models—0
Learning Individualized Cardiovascular Responses from Large-scale Wearable Sensors Data—0
Modeling Treatment Delays for Patients using Feature Label Pairs in a Time Series—0
Large Spectral Density Matrix Estimation by Thresholding—0
Show:102550
← PrevPage 210 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