15 citations · 27 across the 4 of their papers we have counts for
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stat.ML2020★ 7 cited
Efficient Variational Inference for Sparse Deep Learning with Theoretical Guarantee
Jincheng Bai, Qifan Song, Guang Cheng
Sparse deep learning aims to address the challenge of huge storage consumption by deep neural networks, and to recover the sparse structure of target functions. Although tremendous…
stat.ML2020★ 4 cited
Nearly Optimal Variational Inference for High Dimensional Regression with Shrinkage Priors
Jincheng Bai, Qifan Song, Guang Cheng
We propose a variational Bayesian (VB) procedure for high-dimensional linear model inferences with heavy tail shrinkage priors, such as student-t prior. Theoretically, we establish…
stat.ML2018★ 15 cited
Stein Neural Sampler
Tianyang Hu, Zixiang Chen, Hanxi Sun +3
We propose two novel samplers to generate high-quality samples from a given (un-normalized) probability density. Motivated by the success of generative adversarial networks, we con…