48 citations · 153 across the 26 of their papers we have counts for
26 papers
A Double Regression Method for Graphical Modeling of High-dimensional Nonlinear and Non-Gaussian Data
Siqi Liang, Faming Liang
Graphical models have long been studied in statistics as a tool for inferring conditional independence relationships among a large set of random variables. The most existing works…
Non-reversible Parallel Tempering for Deep Posterior Approximation
Wei Deng, Qian Zhang, Qi Feng +2
Parallel tempering (PT), also known as replica exchange, is the go-to workhorse for simulations of multi-modal distributions. The key to the success of PT is to adopt efficient swa…
Nonlinear Sufficient Dimension Reduction with a Stochastic Neural Network
Siqi Liang, Yan Sun, Faming Liang
Sufficient dimension reduction is a powerful tool to extract core information hidden in the high-dimensional data and has potentially many important applications in machine learnin…
Interacting Contour Stochastic Gradient Langevin Dynamics
Wei Deng, Siqi Liang, Botao Hao +2
We propose an interacting contour stochastic gradient Langevin dynamics (ICSGLD) sampler, an embarrassingly parallel multiple-chain contour stochastic gradient Langevin dynamics (C…
A Kernel-Expanded Stochastic Neural Network
Yan Sun, Faming Liang
The deep neural network suffers from many fundamental issues in machine learning. For example, it often gets trapped into a local minimum in training, and its prediction uncertaint…
Sparse Deep Learning: A New Framework Immune to Local Traps and Miscalibration
Yan Sun, Wenjun Xiong, Faming Liang
Deep learning has powered recent successes of artificial intelligence (AI). However, the deep neural network, as the basic model of deep learning, has suffered from issues such as…