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

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Showing 2301–2350 of 6748 papers

TitleStatusHype
Nowcasting the Financial Time Series with Streaming Data Analytics under Apache Spark—0
Neural Generalised AutoRegressive Conditional Heteroskedasticity—0
NetRCA: An Effective Network Fault Cause Localization Algorithm—0
NeuroView-RNN: It's About Time—0
DL-SLOT: Dynamic Lidar SLAM and Object Tracking Based On Graph Optimization—0
Simulating Network Paths with Recurrent Buffering Units—0
Learning Dynamics and Structure of Complex Systems Using Graph Neural Networks—0
Macroeconomic Effect of Uncertainty and Financial Shocks: a non-Gaussian VAR approach—0
Estimation of Evaporator Valve Sizes in Supermarket Refrigeration Cabinets—0
Integrated Fault Diagnosis and Control Design for DER Inverters using Machine Learning Methods—0
A Deep Learning Model for Forecasting Global Monthly Mean Sea Surface Temperature Anomalies—0
Recurrent Auto-Encoder With Multi-Resolution Ensemble and Predictive Coding for Multivariate Time-Series Anomaly Detection—0
Time Series Analysis of Blockchain-Based Cryptocurrency Price ChangesCode0
A Novel Anomaly Detection Method for Multimodal WSN Data Flow via a Dynamic Graph Neural Network—0
Simulating User-Level Twitter Activity with XGBoost and Probabilistic Hybrid Models—0
Long Run Risk in Stationary Structural Vector Autoregressive Models—0
PGCN: Progressive Graph Convolutional Networks for Spatial-Temporal Traffic Forecasting—0
Dynamic Relation Discovery and Utilization in Multi-Entity Time Series Forecasting—0
"Back to the future" projections for COVID-19 surgesCode0
SAITS: Self-Attention-based Imputation for Time SeriesCode0
Multi-Objective Model Selection for Time Series Forecasting—0
GRAPHSHAP: Explaining Identity-Aware Graph Classifiers Through the Language of Motifs—0
Level set based particle filter driven by optical flow: an application to track the salt boundary from X-ray CT time-series—0
HDC-MiniROCKET: Explicit Time Encoding in Time Series Classification with Hyperdimensional Computing—0
Auxiliary Cross-Modal Representation Learning with Triplet Loss Functions for Online Handwriting Recognition—0
Multi-View Fusion Transformer for Sensor-Based Human Activity Recognition—0
TimeREISE: Time-series Randomized Evolving Input Sample Explanation—0
A Prospective Approach for Human-to-Human Interaction Recognition from Wi-Fi Channel Data using Attention Bidirectional Gated Recurrent Neural Network with GUI Application Implementation—0
Market-Based Price Autocorrelation—0
Investigating the genomic background of CRISPR-Cas genomes for CRISPR-based antimicrobials—0
ViNTER: Image Narrative Generation with Emotion-Arc-Aware Transformer—0
LIMREF: Local Interpretable Model Agnostic Rule-based Explanations for Forecasting, with an Application to Electricity Smart Meter Data—0
Domain Adaptation with Representation Learning and Nonlinear Relation for Time SeriesCode0
Benchmarking Online Sequence-to-Sequence and Character-based Handwriting Recognition from IMU-Enhanced Pens—0
Simple Models and Biased Forecasts—0
Recurrent Neural Networks for Dynamical Systems: Applications to Ordinary Differential Equations, Collective Motion, and Hydrological Modeling—0
Vau da muntanialas: Energy-efficient multi-die scalable acceleration of RNN inference—0
Statistical Inference for the Dynamic Time Warping Distance, with Application to Abnormal Time-Series Detection—0
Sequential Monte Carlo With Model Tempering—0
Local approximation of operators—0
Feature Construction and Selection for PV Solar Power Modeling—0
Fitting Sparse Markov Models to Categorical Time Series Using Regularization—0
Wind power ramp prediction algorithm based on wavelet deep belief network—0
SleepPPG-Net: a deep learning algorithm for robust sleep staging from continuous photoplethysmography—0
Active Privacy-Utility Trade-off Against Inference in Time-Series Data Sharing—0
Hybridization of Capsule and LSTM Networks for unsupervised anomaly detection on multivariate data—0
Learning Latent Causal Dynamics—0
Case-based reasoning for rare events prediction on strategic sites—0
Two-Stage Deep Anomaly Detection with Heterogeneous Time Series Data—0
Ketamine-Medetomidine General Anesthesia Occurs With Alternation of Cortical Electrophysiological Activity Between High and Low Complex States—0
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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