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TitleStatusHype
The boosted HP filter is more general than you might think0
A Comparative Study of Sentence Embedding Models for Assessing Semantic Variation0
Inductive Predictions of Extreme Hydrologic Events in The Wabash River Watershed0
The Canonical Interval Forest (CIF) Classifier for Time Series Classification0
Data-generating process and time-series asset pricing0
The Case for Temporal Transparency: Detecting Policy Change Events in Black-Box Decision Making Systems0
Inductive Granger Causal Modeling for Multivariate Time Series0
Indoor Localization Using Smartphone Magnetic with Multi-Scale TCN and LSTM0
The Computational Capacity of LRC, Memristive and Hybrid Reservoirs0
Data-Folding and Hyperspace Coding for Multi-Dimensonal Time-Series Data Imaging0
A Renormalization Group Approach to Connect Discrete- and Continuous-Time Descriptions of Gaussian Processes0
Attention and Autoencoder Hybrid Model for Unsupervised Online Anomaly Detection0
The Creation and Validation of Load Time Series for Synthetic Electric Power Systems0
Indoor environment data time-series reconstruction using autoencoder neural networks0
The data synergy effects of time-series deep learning models in hydrology0
Individual Topology Structure of Eye Movement Trajectories0
Individualized Time-Series Segmentation for Mining Mobile Phone User Behavior0
Data Exploration and Validation on dense knowledge graphs for biomedical research0
The DOPE Distance is SIC: A Stable, Informative, and Computable Metric on Time Series And Ordered Merge Trees0
The dual frequency RV-coupling coefficient: a novel measure for quantifying cross-frequency information transactions in the brain0
The Dynamical Gaussian Process Latent Variable Model in the Longitudinal Scenario0
Analysis of Distributional Dynamics for Repeated Cross-Sectional and Intra-Period Observations0
Evolutionary Dynamics of Investors Expectations and Market Price Movement0
Individualized Dynamic Latent Factor Model for Multi-resolutional Data with Application to Mobile Health0
Individualised recovery trajectories of patients with impeded mobility, using distance between probability distributions of learnt graphs0
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