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06/01/2023
From sparse to dense functional data in high dimensions: Revisiting phase transitions from a non-asymptotic perspective
Nonparametric estimation of the mean and covariance functions is ubiquit...
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05/23/2023
DF2M: An Explainable Deep Bayesian Nonparametric Model for High-Dimensional Functional Time Series
In this paper, we present Deep Functional Factor Model (DF2M), a Bayesia...
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08/12/2022
EEGNN: Edge Enhanced Graph Neural Networks
Training deep graph neural networks (GNNs) poses a challenging task, as ...
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07/14/2022
Adaptive Functional Thresholding for Sparse Covariance Function Estimation in High Dimensions
Covariance function estimation is a fundamental task in multivariate fun...
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12/27/2021
Factor modelling for high-dimensional functional time series
Many economic and scientific problems involve the analysis of high-dimen...
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08/29/2020
An autocovariance-based learning framework for high-dimensional functional time series
Many scientific and economic applications involve the analysis of high-d...
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04/16/2020
A New Perspective on Dependence in High-Dimensional Functional/Scalar Time Series: Finite Sample Theory and Applications
Statistical analysis of high-dimensional functional times series arises ...
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03/23/2020
On Consistency and Sparsity for High-Dimensional Functional Time Series with Application to Autoregressions
Modelling a large collection of functional time series arises in a broad...
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01/13/2020
Conditional Variational Inference with Adaptive Truncation for Bayesian Nonparametric Models
The scalable inference for Bayesian nonparametric models with big data i...
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12/18/2018
A General Theory for Large-Scale Curve Time Series via Functional Stability Measure
Modelling a large bundle of curves arises in a broad spectrum of real ap...
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06/14/2018