Liang, Faming

15 publications

TMLR 2025 Latent Trajectory: A New Framework for Deep Actor-Critic Reinforcement Learning with Uncertainty Quantification Frank Shih, Faming Liang

NeurIPS 2025 Uncertainty Quantification for Physics-Informed Neural Networks with Extended Fiducial Inference Frank Shih, Zhenghao Jiang, Faming Liang

ICLR 2024 Causal-StoNet: Causal Inference for High-Dimensional Complex Data Yaxin Fang, Faming Liang

ICLR 2024 Fast Value Tracking for Deep Reinforcement Learning Frank Shih, Faming Liang

AAAI 2023 Non-Reversible Parallel Tempering for Deep Posterior Approximation Wei Deng, Qian Zhang, Qi Feng, Faming Liang, Guang Lin

NeurIPS 2023 Sparse Deep Learning for Time Series Data: Theory and Applications Mingxuan Zhang, Yan Sun, Faming Liang

ICLR 2022 Interacting Contour Stochastic Gradient Langevin Dynamics Wei Deng, Siqi Liang, Botao Hao, Guang Lin, Faming Liang

NeurIPS 2022 Nonlinear Sufficient Dimension Reduction with a Stochastic Neural Network Siqi Liang, Yan Sun, Faming Liang

ICLR 2021 Accelerating Convergence of Replica Exchange Stochastic Gradient MCMC via Variance Reduction Wei Deng, Qi Feng, Georgios P. Karagiannis, Guang Lin, Faming Liang

NeurIPS 2021 Sparse Deep Learning: A New Framework Immune to Local Traps and Miscalibration Yan Sun, Wenjun Xiong, Faming Liang

NeurIPS 2020 A Contour Stochastic Gradient Langevin Dynamics Algorithm for Simulations of Multi-Modal Distributions Wei Deng, Guang Lin, Faming Liang

ICML 2020 Non-Convex Learning via Replica Exchange Stochastic Gradient MCMC Wei Deng, Qi Feng, Liyao Gao, Faming Liang, Guang Lin

NeurIPS 2019 An Adaptive Empirical Bayesian Method for Sparse Deep Learning Wei Deng, Xiao Zhang, Faming Liang, Guang Lin

MLJ 2007 Annealing Stochastic Approximation Monte Carlo Algorithm for Neural Network Training Faming Liang

NeCo 2003 An Effective Bayesian Neural Network Classifier with a Comparison Study to Support Vector Machine Faming Liang