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stat.ML2025
Likelihood-Free Variational Autoencoders
Chen Xu, Qiang Wang, Lijun Sun
Variational Autoencoders (VAEs) typically rely on a probabilistic decoder with a predefined likelihood, most commonly an isotropic Gaussian, to model the data conditional on latent…
stat.ML2024
Better Batch for Deep Probabilistic Time Series Forecasting
Vincent Zhihao Zheng, Seongjin Choi, Lijun Sun
Deep probabilistic time series forecasting has gained attention for its ability to provide nonlinear approximation and valuable uncertainty quantification for decision-making. Howe…
stat.ML2024
Scalable Spatiotemporally Varying Coefficient Modelling with Bayesian Kernelized Tensor Regression
Mengying Lei, Aurelie Labbe, Lijun Sun
As a regression technique in spatial statistics, the spatiotemporally varying coefficient model (STVC) is an important tool for discovering nonstationary and interpretable response…