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 1501–1550 of 6748 papers

TitleStatusHype
Deep learning delay coordinate dynamics for chaotic attractors from partial observable data—0
Estimating Task Completion Times for Network Rollouts using Statistical Models within Partitioning-based Regression Methods—0
Machine Learning Methods for Anomaly Detection in Nuclear Power Plant Power Transformers—0
Autoregressive GNN-ODE GRU Model for Network Dynamics—0
Class-Specific Attention (CSA) for Time-Series Classification—0
Step Counting with Attention-based LSTMCode0
A Transformer Framework for Data Fusion and Multi-Task Learning in Smart CitiesCode0
Fractional integration and cointegration—0
Identifying Unique Causal Network from Nonstationary Time SeriesCode0
Neural Inference of Gaussian Processes for Time Series Data of QuasarsCode0
Cointegration with Occasionally Binding Constraints—0
DSLOB: A Synthetic Limit Order Book Dataset for Benchmarking Forecasting Algorithms under Distributional Shift—0
Parameterization of state duration in Hidden semi-Markov Models: an application in electrocardiography—0
Imputation of Missing Streamflow Data at Multiple Gauging Stations in Benin Republic—0
Graph Filters for Signal Processing and Machine Learning on Graphs—0
Data-driven Real-time Short-term Prediction of Air Quality: Comparison of ES, ARIMA, and LSTM—0
Ischemic Stroke Lesion Prediction using imbalanced Temporal Deep Gaussian Process (iTDGP)—0
Hierarchical Estimation for Effective and Efficient Sampling Graph Neural Network—0
HGV4Risk: Hierarchical Global View-guided Sequence Representation Learning for Risk PredictionCode0
Parameter-Covariance Maximum Likelihood Estimation—0
Motor imagery classification using EEG spectrograms—0
Temporal patterns in insulin needs for Type 1 diabetesCode0
Multi-VQG: Generating Engaging Questions for Multiple ImagesCode0
HigeNet: A Highly Efficient Modeling for Long Sequence Time Series Prediction in AIOpsCode0
Similarity-based Feature Extraction for Large-scale Sparse Traffic ForecastingCode0
Data Quality Over Quantity: Pitfalls and Guidelines for Process Analytics—0
Comparison of Uncertainty Quantification with Deep Learning in Time Series Regression—0
Accounting for Temporal Variability in Functional Magnetic Resonance Imaging Improves Prediction of IntelligenceCode0
Spatial Temporal Graph Convolution with Graph Structure Self-learning for Early MCI Detection—0
Investigating Enhancements to Contrastive Predictive Coding for Human Activity RecognitionCode0
Does Deep Learning REALLY Outperform Non-deep Machine Learning for Clinical Prediction on Physiological Time Series?—0
Variance of entropy for testing time-varying regimes with an application to meme stocks—0
Driver Maneuver Detection and Analysis using Time Series Segmentation and Classification—0
A Graph Neural Networks based Framework for Topology-Aware Proactive SLA Management in a Latency Critical NFV Application Use-case—0
Bayesian Neural Networks for Macroeconomic Analysis—0
Detecting Elevated Air Pollution Levels by Monitoring Web Search Queries: Deep Learning-Based Time Series Forecasting—0
Towards Global Crop Maps with Transfer Learning—0
Active queue management: First steps toward a new control-theoretic viewpoint—0
TimeKit: A Time-series Forecasting-based Upgrade Kit for Collaborative Filtering—0
Reduced Order Probabilistic Emulation for Physics-Based Thermosphere ModelsCode0
Dynamic Interpretable Change Point Detection—0
Motif-guided Time Series Counterfactual Explanations—0
Privacy Meets Explainability: A Comprehensive Impact Benchmark—0
Quantum Persistent Homology for Time Series—0
Latent Neural ODE for Integrating Multi-timescale measurements in Smart Distribution Grids—0
Minimax Concave Penalty Regularized Adaptive System Identification—0
FIXED: Frustratingly Easy Domain Generalization with Mixup—0
A Synthetic Dataset for 5G UAV Attacks Based on Observable Network Parameters—0
Accurate and Reliable Methods for 5G UAV Jamming Identification With Calibrated Uncertainty—0
Discovering ordinary differential equations that govern time-series—0
Show:102550
← PrevPage 31 of 135Next →
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