Exact sequential test of equivalence hypothesis based on bivariate non-central t-statistics. - Fang Liu 006; Qing Li (Comput. Stat. Data Anal., 2014)

gset: An R Package for Exact Sequential Test of Equivalence Hypothesis Based on Bivariate Non-Central t-Statistics. - Fang Liu 006 (R J., 2014)

zoib: An R Package for Bayesian Inference for Beta Regression and Zero/One Inflated Beta Regression. - Fang Liu 006; Yunchuan Kong (R J., 2015)

Noninformative Bounding in Differential Privacy and Its Impact on Statistical Properties of Sanitized Results in Truncated and Boundary-Inflated-Truncated Laplace Mechanisms. - Fang Liu 006 (CoRR, 2016)

一种基于概率粗糙集的属性约简加速算法 (Accelerated Attribute Reduction Algorithm Based on Probabilistic Rough Sets). - Fang Liu 006; Tianrui Li 001 (计算机科学, 2016)

基于边界域的不完备信息系统属性约简方法 (Method for Attribute Reduction Based on Rough Sets Boundary Regions). - Fang Liu 006; Tianrui Li 001 (计算机科学, 2016)

Panda: AdaPtive Noisy Data Augmentation for Regularization of Undirected Graphical Models. - Yinan Li; Xiao Liu; Fang Liu 006 (CoRR, 2018)

CIPHER: Construction of dIfferentially Private microdata from low-dimensional Histograms via solving linear Equations with Tikhonov Regularization. - Evercita C. Eugenio; Fang Liu 006 (CoRR, 2018)

Statistical Properties of Sanitized Results from Differentially Private Laplace Mechanism with Univariate Bounding Constraints. - Fang Liu 006 (Trans. Data Priv., 2019)

Generalized Gaussian Mechanism for Differential Privacy. - Fang Liu 006 (IEEE Trans. Knowl. Data Eng., 2019)

Differentially Private Generation of Social Networks via Exponential Random Graph Models. - Fang Liu 006; Evercita C. Eugenio; Ick-Hoon Jin; Claire McKay Bowen (COMPSAC, 2020)

Adaptive Gaussian Noise Injection Regularization for Neural Networks. - Yinan Li; Fang Liu 006 (ISNN, 2020)

Adaptive Noisy Data Augmentation for Regularized Construction of Undirected Graphical Models. - Yinan Li; Fang Liu 006; Xiao Liu (DSAA, 2021)

Continuous-Time Markov-Switching GARCH Process with Robust State Path Identification and Volatility Estimation. - Yinan Li; Fang Liu 006 (ECML/PKDD (1), 2021)

Construction of Differentially Private Empirical Distributions from a Low-Order Marginals Set Through Solving Linear Equations with l2 Regularization. - Evercita C. Eugenio; Fang Liu 006 (SAI (3), 2021)

Improved MABAC method based on single-valued neutrosophic 2-tuple linguistic sets and Frank aggregation operators for MAGDM. - Lei Xu 042; Yi Liu 005; Fang Liu 006 (Comput. Appl. Math., 2021)

Sentiment Analysis and Effect of COVID-19 Pandemic using College SubReddit Data. - Tian Yan; Fang Liu 006 (CoRR, 2021)

Multiple Attribute Decision-Making Method Based upon Intuitionistic Fuzzy Partitioned Dual Maclaurin Symmetric Mean Operators. - Hongjuan Wang; Yi Liu 005; Fang Liu 006; Jun Lin (Int. J. Comput. Intell. Syst., 2021)

Three-way decisions with decision-theoretic rough sets based on covering-based q-rung orthopair fuzzy rough set model. - Fang Liu 006; Yi Liu 005; Saleem Abdullah (J. Intell. Fuzzy Syst., 2021)

Modification of the BWM and MABAC method for MAGDM based on q-rung orthopair fuzzy rough numbers. - Fang Liu 006; Tianrui Li 001; Ju Wu; Yi Liu 005 (Int. J. Mach. Learn. Cybern., 2021)

Disclosure Risk from Homogeneity Attack in Differentially Private Release of Frequency Distribution. - Fang Liu 006; Xingyuan Zhao (CODASPY, 2022)

A New Bound for Privacy Loss from Bayesian Posterior Sampling. - Xingyuan Zhao; Fang Liu 006 (CODASPY, 2022)

Adaptive Noisy Data Augmentation for Regularized Estimation and Inference of Generalized Linear Models. - Yinan Li; Fang Liu 006 (COMPSAC, 2022)

Efficient Reinforcement Learning from Demonstration Using Local Ensemble and Reparameterization with Split and Merge of Expert Policies. - Yu Wang; Fang Liu 006 (COMPSAC, 2022)

Noise-Augmented Privacy-Preserving Empirical Risk Minimization with Dual-Purpose Regularizer and Privacy Budget Retrieval and Recycling. - Yinan Li; Fang Liu 006 (SAI (3), 2022)

AdaAnn: Adaptive Annealing Scheduler for Probability Density Approximation. - Emma R. Cobian; Jonathan D. Hauenstein; Fang Liu 006; Daniele E. Schiavazzi (CoRR, 2022)

Variational inference with NoFAS: Normalizing flow with adaptive surrogate for computationally expensive models. - Yu Wang; Fang Liu 006; Daniele E. Schiavazzi (J. Comput. Phys., 2022)

Differentially Private Normalizing Flows for Density Estimation, Data Synthesis, and Variational Inference with Application to Electronic Health Records. - Bingyue Su; Yu Wang; Daniele E. Schiavazzi; Fang Liu 006 (CoRR, 2023)

Has Sentiment Returned to the Pre-pandemic Level? A Sentiment Analysis Using U.S. College Subreddit Data from 2019 to 2022. - Tian Yan; Fang Liu 006 (CoRR, 2023)

GIBWM-MABAC approach for MAGDM under multi-granularity intuitionistic 2-tuple linguistic information model. - Yi Liu 005; Ya Qin; Fang Liu 006; Yuan Rong (J. Ambient Intell. Humaniz. Comput., 2023)

Disclosure Risk From Homogeneity Attack in Differentially Privately Sanitized Frequency Distribution. - Fang Liu 006; Xingyuan Zhao (IEEE Trans. Dependable Secur. Comput., 2023)

Privacy-Preserving Travel Time Prediction With Uncertainty Using GPS Trace Data. - Fang Liu 006; Dong Wang 019; Zhengquan Xu (IEEE Trans. Mob. Comput., 2023)

Risk Assessment of Open-Pit Slope Based on Large-Scale Group Decision-Making Method Considering Non-Cooperative Behavior. - Ju Wu; Hao Gong; Fang Liu 006; Yi Liu 005 (Int. J. Fuzzy Syst., 2023)

LINFA: a Python library for variational inference with normalizing flow and annealing. - Yu Wang; Emma R. Cobian; Jubilee Lee; Fang Liu 006; Jonathan D. Hauenstein; Daniele E. Schiavazzi (J. Open Source Softw., 2024)

Location Selection for Dry Hot Rock Exploration Based on Large-Scale Group Decision-Making with Three-way Decision. - Fang Liu 006; Zhongli Zhou; Ju Wu; Yi Liu 005 (Int. J. Fuzzy Syst., 2024)

Noise-Augmented ℓ 0 Regularization of Tensor Regression With Tucker Decomposition. - Tian Yan; Yinan Li; Fang Liu 006 (Stat. Anal. Data Min., 2025)