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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 3301–3350 of 6748 papers

TitleStatusHype
Influential Node Detection in Implicit Social Networks using Multi-task Gaussian Copula Models—0
InfoCNF: An Efficient Conditional Continuous Normalizing Flow with Adaptive Solvers—0
Complex systems approach to natural language—0
Infomaxformer: Maximum Entropy Transformer for Long Time-Series Forecasting Problem—0
Information-Aware Time Series Meta-Contrastive Learning—0
Information flow networks of Chinese stock market sectors—0
Information theoretical study of cross-talk mediated signal transduction in MAPK pathways—0
Information Theoretic Measures of Causal Influences during Transient Neural Events—0
Information Theory Inspired Pattern Analysis for Time-series Data—0
A Review on Deep Learning in UAV Remote Sensing—0
Complex market dynamics in the light of random matrix theory—0
Complexity Measures and Features for Times Series classification—0
Initial conditions in the neural field model—0
Initialising Kernel Adaptive Filters via Probabilistic Inference—0
A Review of Wind Speed and Wind Power Forecasting Techniques—0
Initialization of multilayer forecasting artifical neural networks—0
A Method for Estimating the Entropy of Time Series Using Artificial Neural Networks—0
Injecting Explainability and Lightweight Design into Weakly Supervised Video Anomaly Detection Systems—0
Forecasting with a Panel Tobit Model—0
Forecasting Using Reservoir Computing: The Role of Generalized Synchronization—0
Innovative Second-Generation Wavelets Construction With Recurrent Neural Networks for Solar Radiation Forecasting—0
Complexity-based Financial Stress Evaluation—0
Forecasting under Long Memory and Nonstationarity—0
In Search of Deep Learning Architectures for Load Forecasting: A Comparative Analysis and the Impact of the Covid-19 Pandemic on Model Performance—0
Forecasting trends with asset prices—0
Complexity and Persistence of Price Time Series of the European Electricity Spot Market—0
Forecasting Time Series with VARMA Recursions on Graphs—0
In-situ animal behavior classification using knowledge distillation and fixed-point quantization—0
Forecasting time series with encoder-decoder neural networks—0
Inspection of methods of empirical mode decomposition—0
Forecasting the Turkish Lira Exchange Rates through Univariate Techniques: Can the Simple Models Outperform the Sophisticated Ones?—0
Compensatory model for quantile estimation and application to VaR—0
A review of two decades of correlations, hierarchies, networks and clustering in financial markets—0
A Metamodel and Framework for Artificial General Intelligence From Theory to Practice—0
NeurIPS Competition Instructions and Guide: Causal Insights for Learning Paths in Education—0
Integer Echo State Networks: Efficient Reservoir Computing for Digital Hardware—0
Integrated Fault Diagnosis and Control Design for DER Inverters using Machine Learning Methods—0
Integrated information and dimensionality in continuous attractor dynamics—0
Forecasting Thermoacoustic Instabilities in Liquid Propellant Rocket Engines Using Multimodal Bayesian Deep Learning—0
Forecasting the production of Distillate Fuel Oil Refinery and Propane Blender net production by using Time Series Algorithms—0
Forecasting The JSE Top 40 Using Long Short-Term Memory Networks—0
Integrating Domain Knowledge in Data-driven Earth Observation with Process Convolutions—0
A review of predictive uncertainty estimation with machine learning—0
Forecasting the abnormal events at well drilling with machine learning—0
Integrating Physiological Time Series and Clinical Notes with Transformer for Early Prediction of Sepsis—0
Forecasting Spatio-Temporal Renewable Scenarios: a Deep Generative Approach—0
Comparison of Uncertainty Quantification with Deep Learning in Time Series Regression—0
Forecasting Solar Power Generation on the basis of Predictive and Corrective Maintenance Activities—0
Local-Global Methods for Generalised Solar Irradiance Forecasting—0
Comparison of Traditional and Hybrid Time Series Models for Forecasting COVID-19 Cases—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