Faming Liang | DeepAI

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Featured Co-authors

Yang Yang
251 publications
Qian Zhang
144 publications
Xiao Zhang
60 publications
Guang Lin
56 publications
Tianhao Wang
49 publications
Mao Ye
37 publications
Yan Sun
36 publications
Botao Hao
23 publications
Qifan Song
23 publications
Ninghui Li
21 publications
Ye Luo
21 publications

∙ 12/08/2022

A Double Regression Method for Graphical Modeling of High-dimensional Nonlinear and Non-Gaussian Data

Graphical models have long been studied in statistics as a tool for infe...

0 Siqi Liang, et al. ∙

∙ 11/20/2022

Non-reversible Parallel Tempering for Deep Posterior Approximation

Parallel tempering (PT), also known as replica exchange, is the go-to wo...

0 Wei Deng, et al. ∙

∙ 10/09/2022

Nonlinear Sufficient Dimension Reduction with a Stochastic Neural Network

Sufficient dimension reduction is a powerful tool to extract core inform...

0 Siqi Liang, et al. ∙

∙ 02/20/2022

Interacting Contour Stochastic Gradient Langevin Dynamics

We propose an interacting contour stochastic gradient Langevin dynamics ...

0 Wei Deng, et al. ∙

∙ 01/14/2022

A Kernel-Expanded Stochastic Neural Network

The deep neural network suffers from many fundamental issues in machine ...

0 Yan Sun, et al. ∙

∙ 10/01/2021

Sparse Deep Learning: A New Framework Immune to Local Traps and Miscalibration

Deep learning has powered recent successes of artificial intelligence (A...

0 Yan Sun, et al. ∙

∙ 05/11/2021

A Langevinized Ensemble Kalman Filter for Large-Scale Static and Dynamic Learning

The Ensemble Kalman Filter (EnKF) has achieved great successes in data a...

0 Peiyi Zhang, et al. ∙

∙ 02/25/2021

Consistent Sparse Deep Learning: Theory and Computation

Deep learning has been the engine powering many successes of data scienc...

0 Yan Sun, et al. ∙

∙ 12/17/2020

PURE: A Framework for Analyzing Proximity-based Contact Tracing Protocols

Many proximity-based tracing (PCT) protocols have been proposed and depl...

0 Fabrizio Cicala, et al. ∙

∙ 10/19/2020

A Contour Stochastic Gradient Langevin Dynamics Algorithm for Simulations of Multi-modal Distributions

We propose an adaptively weighted stochastic gradient Langevin dynamics ...

0 Wei Deng, et al. ∙

∙ 10/17/2020

Markov Neighborhood Regression for High-Dimensional Inference

This paper proposes an innovative method for constructing confidence int...

0 Faming Liang, et al. ∙

∙ 10/02/2020

Accelerating Convergence of Replica Exchange Stochastic Gradient MCMC via Variance Reduction

Replica exchange stochastic gradient Langevin dynamics (reSGLD) has show...

8 Wei Deng, et al. ∙

∙ 09/20/2020

Stochastic Gradient Langevin Dynamics Algorithms with Adaptive Drifts

Bayesian deep learning offers a principled way to address many issues co...

0 Sehwan Kim, et al. ∙

∙ 08/12/2020

Non-convex Learning via Replica Exchange Stochastic Gradient MCMC

Replica exchange Monte Carlo (reMC), also known as parallel tempering, i...

12 Wei Deng, et al. ∙

∙ 02/07/2020

Extended Stochastic Gradient MCMC for Large-Scale Bayesian Variable Selection

Stochastic gradient Markov chain Monte Carlo (MCMC) algorithms have rece...

0 Qifan Song, et al. ∙

∙ 10/23/2019

An Adaptive Empirical Bayesian Method for Sparse Deep Learning

We propose a novel adaptive empirical Bayesian (AEB) method for sparse d...

0 Wei Deng, et al. ∙

∙ 10/11/2018

Stochastic Approximation Hamiltonian Monte Carlo

Recently, the Hamilton Monte Carlo (HMC) has become widespread as one of...

0 Ick Hoon Jin, et al. ∙

∙ 05/07/2018

Learning Multiple Gene Regulatory Networks in Type 1 Diabetes through a Fast Bayesian Integrative Method

Accurate inference of Gene Regulatory Networks (GRNs) is pivotal to gain...

0 Bochao Jia, et al. ∙

∙ 05/07/2018

Learning Gene Regulatory Networks with High-Dimensional Heterogeneous Data

The Gaussian graphical model is a widely used tool for learning gene reg...

0 Bochao Jia, et al. ∙

∙ 02/22/2018

A Bayesian Mark Interaction Model for Analysis of Tumor Pathology Images

With the advance of imaging technology, digital pathology imaging of tum...

0 Qiwei Li, et al. ∙

∙ 02/06/2018

An Imputation-Consistency Algorithm for High-Dimensional Missing Data Problems and Beyond

Missing data are frequently encountered in high-dimensional problems, bu...

0 Faming Liang, et al. ∙

∙ 12/24/2017

Nearly optimal Bayesian Shrinkage for High Dimensional Regression

During the past decade, shrinkage priors have received much attention in...

0 Qifan Song, et al. ∙

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