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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

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Showing 2101–2125 of 6748 papers

TitleStatusHype
Are Chinese transport policies effective? A new perspective from direct pollution rebound effect, and empirical evidence from road transport sector—0
Combining Embeddings and Fuzzy Time Series for High-Dimensional Time Series Forecasting in Internet of Energy Applications—0
Combining Deep Transfer Learning with Signal-image Encoding for Multi-Modal Mental Wellbeing Classification—0
Architectural Tricks for Deep Learning in Remote Photoplethysmography—0
Adaptive Sequential Design for a Single Time-Series—0
Architectural Optimization and Feature Learning for High-Dimensional Time Series Datasets—0
Combined Unbalanced Distribution System State and Line Impedance Matrix Estimation—0
Accurate and Reliable Methods for 5G UAV Jamming Identification With Calibrated Uncertainty—0
COMBINED FLEXIBLE ACTIVATION FUNCTIONS FOR DEEP NEURAL NETWORKS—0
A Machine Learning approach to Risk Minimisation in Electricity Markets with Coregionalized Sparse Gaussian Processes—0
Efficient Calibration of Multi-Agent Simulation Models from Output Series with Bayesian Optimization—0
Efficient combination of pairswise feature networks—0
Combating Uncertainties in Wind and Distributed PV Energy Sources Using Integrated Reinforcement Learning and Time-Series Forecasting—0
Coloured noise time series as appropriate models for environmental variation in artificial evolutionary systems—0
A quantum generative model for multi-dimensional time series using Hamiltonian learning—0
Collective Awareness for Abnormality Detection in Connected Autonomous Vehicles—0
A Quantum Field Theory of Representation Learning—0
A machine learning approach to itinerary-level booking prediction in competitive airline markets—0
Collective Anomaly Detection based on Long Short Term Memory Recurrent Neural Network—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
Collapsed Amortized Variational Inference for Switching Nonlinear Dynamical Systems—0
Collaborative Multiobjective Evolutionary Algorithms in search of better Pareto Fronts. An application to trading systems—0
A proposal of a methodological framework with experimental guidelines to investigate clustering stability on financial time series—0
A Machine Learning Approach for Smartphone-based Sensing of Roads and Driving Style—0
Adaptive Sampling for Probabilistic Forecasting under Distribution Shift—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