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04/08/2023
Efficient Multimodal Sampling via Tempered Distribution Flow
Sampling from high-dimensional distributions is a fundamental problem in...
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02/23/2023
Learning Manifold Dimensions with Conditional Variational Autoencoders
Although the variational autoencoder (VAE) and its conditional extension...
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05/11/2022
Learning Multitask Gaussian Bayesian Networks
Major depressive disorder (MDD) requires study of brain functional conne...
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04/25/2020
Randomized spectral co-clustering for large-scale directed networks
Directed networks are generally used to represent asymmetric relationshi...
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02/13/2020
Stochastic Approximate Gradient Descent via the Langevin Algorithm
We introduce a novel and efficient algorithm called the stochastic appro...
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11/19/2019
Gradient-based Sparse Principal Component Analysis with Extensions to Online Learning
Sparse principal component analysis (PCA) is an important technique for ...
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02/12/2018
Exact and efficient inference for Partial Bayes problems
Bayesian methods are useful for statistical inference. However, real-wor...
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12/29/2017