An EM algorithm for learning sparse and overcomplete representations. - Mingjun Zhong; Huanwen Tang; Hongjun Chen; Yiyuan Tang (Neurocomputing, 2004)

Expectation-Maximization approaches to independent component analysis. - Mingjun Zhong; Huanwen Tang; Yiyuan Tang (Neurocomputing, 2004)

Data Integration for Classification Problems Employing Gaussian Process Priors. - Mark A. Girolami; Mingjun Zhong (NIPS, 2006)

A variational method for learning sparse Bayesian regression. - Mingjun Zhong (Neurocomputing, 2006)

A parametric density model for blind source separation. - Mingjun Zhong; Junfu Du (Neural Process. Lett., 2007)

Scale-free network model under exogenous pressures. - Qiang Guo; Jian-Guo Liu; Mingjun Zhong (Int. J. Model. Identif. Control., 2008)

Classifying EEG for brain computer interfaces using Gaussian processes. - Mingjun Zhong; Fabien Lotte; Mark A. Girolami; Anatole Lécuyer (Pattern Recognit. Lett., 2008)

Reversible Jump MCMC for Non-Negative Matrix Factorization. - Mingjun Zhong; Mark A. Girolami (AISTATS, 2009)

A Bayesian Approach to Approximate Joint Diagonalization of Square Matrices. - Mingjun Zhong; Mark A. Girolami (ICML, 2012)

Bayesian Analysis for miRNA and mRNA Interactions Using Expression Data - Mingjun Zhong; Rong Liu; Bo Liu (CoRR, 2012)

A comparative evaluation of stochastic-based inference methods for Gaussian process models. - Maurizio Filippone; Mingjun Zhong; Mark A. Girolami (Mach. Learn., 2013)

Signal Aggregate Constraints in Additive Factorial HMMs, with Application to Energy Disaggregation. - Mingjun Zhong; Nigel H. Goddard; Charles Sutton (NIPS, 2014)

Latent Bayesian melding for integrating individual and population models. - Mingjun Zhong; Nigel H. Goddard; Charles Sutton (NIPS, 2015)

Classification of Normal/Abnormal Heart Sound Recordings based on Multi-Domain Features and Back Propagation Neural Network. - Hong Tang 001; Huaming Chen; Ting Li 002; Mingjun Zhong (CinC, 2016)

Sequence-to-point learning with neural networks for nonintrusive load monitoring. - Chaoyun Zhang; Mingjun Zhong; Zongzuo Wang; Nigel H. Goddard; Charles Sutton (CoRR, 2016)

Pseudo-marginal Markov Chain Monte Carlo for Nonnegative Matrix Factorization. - Junfu Du; Mingjun Zhong (Neural Process. Lett., 2017)

Sequence-to-Point Learning With Neural Networks for Non-Intrusive Load Monitoring. - Chaoyun Zhang; Mingjun Zhong; Zongzuo Wang; Nigel H. Goddard; Charles Sutton (AAAI, 2018)

Efficient Gradient-Free Variational Inference using Policy Search. - Oleg Arenz; Mingjun Zhong; Gerhard Neumann (ICML, 2018)

Neural Control Variates for Variance Reduction. - Zhanxing Zhu; Ruosi Wan; Mingjun Zhong (CoRR, 2018)

A Hyperplane Clustering Algorithm for Estimating the Mixing Matrix in Sparse Component Analysis. - Xu Xu; Mingjun Zhong; Chonghui Guo (Neural Process. Lett., 2018)

Neural Control Variates for Monte Carlo Variance Reduction. - Ruosi Wan; Mingjun Zhong; Haoyi Xiong; Zhanxing Zhu (ECML/PKDD (2), 2019)

Towards reproducible state-of-the-art energy disaggregation. - Nipun Batra 001; Rithwik Kukunuri; Ayush Pandey; Raktim Malakar; Rajat Kumar; Odysseas Krystalakos; Mingjun Zhong; Paulo Meira; Oliver Parson (BuildSys, 2019)

A demonstration of reproducible state-of-the-art energy disaggregation using NILMTK. - Nipun Batra 001; Rithwik Kukunuri; Ayush Pandey; Raktim Malakar; Rajat Kumar; Odysseas Krystalakos; Mingjun Zhong; Paulo Meira; Oliver Parson (BuildSys, 2019)

AREA: Adaptive Reference-set Based Evolutionary Algorithm for Multiobjective Optimisation. - Shouyong Jiang; Hongru Li; Jinglei Guo; Mingjun Zhong; Shengxiang Yang; Marcus Kaiser; Natalio Krasnogor (CoRR, 2019)

Lightweight Non-Intrusive Load Monitoring Employing Pruned Sequence-to-Point Learning. - Jack Barber; Heriberto Cuayáhuitl; Mingjun Zhong; Wenpeng Luan (NILM@SenSys, 2020)

AREA: An adaptive reference-set based evolutionary algorithm for multiobjective optimisation. - Shouyong Jiang; Hongru Li; Jinglei Guo; Mingjun Zhong; Shengxiang Yang; Marcus Kaiser; Natalio Krasnogor (Inf. Sci., 2020)

Trust-Region Variational Inference with Gaussian Mixture Models. - Oleg Arenz; Mingjun Zhong; Gerhard Neumann (J. Mach. Learn. Res., 2020)

Transfer Learning for Non-Intrusive Load Monitoring. - Michele D'Incecco; Stefano Squartini; Mingjun Zhong (IEEE Trans. Smart Grid, 2020)

A Top-K QoS-Optimal Service Composition Approach Based on Service Dependency Graph. - Baili Zhang; Kejie Wen; Jianhua Lu; Mingjun Zhong (J. Organ. End User Comput., 2021)

A discrete-time Bayesian network approach for reliability analysis of dynamic systems with common cause failures. - Yongjin Guo; Mingjun Zhong; Chao Gao; Hong Dong Wang; Xiaofeng Liang; Hong Yi (Reliab. Eng. Syst. Saf., 2021)

Causal Effect Estimation Using Variational Information Bottleneck. - Zhenyu Lu; Yurong Cheng; Mingjun Zhong; George Stoian; Ye Yuan 001; Guoren Wang (WISA, 2022)

A Semantic Representation Scheme for Medical Dispute Judgment Documents Based on Elements Extraction. - Siyao An; Tianhao Wang 016; Lirui Wang; Mingjun Zhong; Baili Zhang (ICAIS (2), 2022)

LightNILM: lightweight neural network methods for non-intrusive load monitoring. - Zhenyu Lu; Yurong Cheng; Mingjun Zhong; Wenpeng Luan; Yuan Ye 001; Guoren Wang (BuildSys, 2022)

Algorithms to Calculate the Most Reliable Maximum Flow in Content Delivery Network. - Baili Zhang; Keke Ling; Pei Zhang; Zhao Zhang; Mingjun Zhong (Comput. Syst. Sci. Eng., 2022)

System operational reliability evaluation based on dynamic Bayesian network and XGBoost. - Yongjin Guo; Hongdong Wang; Yu Guo; Mingjun Zhong; Qing Li 050; Chao Gao (Reliab. Eng. Syst. Saf., 2022)

Vanishing Activations: A Symptom of Deep Capsule Networks. - Miles Everett; Mingjun Zhong; Georgios Leontidis (CoRR, 2023)

Semantic Positive Pairs for Enhancing Contrastive Instance Discrimination. - Mohammad Alkhalefi; Georgios Leontidis; Mingjun Zhong (CoRR, 2023)

Nonintrusive Load Monitoring Based on Self-Supervised Learning. - Shuyi Chen; Bochao Zhao; Mingjun Zhong; Wenpeng Luan; Yixin Yu (IEEE Trans. Instrum. Meas., 2023)

ProtoCaps: A Fast and Non-Iterative Capsule Network Routing Method. - Miles Everett; Mingjun Zhong; Georgios Leontidis (Trans. Mach. Learn. Res., 2023)

Lightweight deep learning methods for panoramic dental X-ray image segmentation. - Songyue Lin; Xuejiang Hao; Yan Liu; Dong Yan; Jianwei Liu; Mingjun Zhong (Neural Comput. Appl., 2023)

Capsule Network Projectors are Equivariant and Invariant Learners. - Miles Everett; Aiden Durrant; Mingjun Zhong; Georgios Leontidis (CoRR, 2024)

A Survey of Pipeline Tools for Data Engineering. - Anthony Mbata; Yaji Sripada; Mingjun Zhong (CoRR, 2024)

Semantic Positive Pairs for Enhancing Visual Representation Learning of Instance Discrimination methods. - Mohammad Alkhalefi; Georgios Leontidis; Mingjun Zhong (Trans. Mach. Learn. Res., 2024)

LeOCLR: Leveraging Original Images for Contrastive Learning of Visual Representations. - Mohammad Alkhalefi; Georgios Leontidis; Mingjun Zhong (Trans. Mach. Learn. Res., 2024)

Multisource Domain Adaptation for Nonintrusive Load Monitoring Through Data Distillation. - Wenpeng Luan; Ruiqi Zhang; Bo Liu 072; Mingjun Zhong; Keke Li (IEEE Trans. Instrum. Meas., 2025)

Masked Capsule Autoencoders. - Miles Everett; Mingjun Zhong; Georgios Leontidis (Trans. Mach. Learn. Res., 2025)

FlowETL: An Autonomous Example-Driven Pipeline for Data Engineering. - Mattia Di Profio; Mingjun Zhong; Yaji Sripada; Marcel Jaspars (CoRR, 2025)

OmniNet: an expandable causal inference network for multiple modalities. - Yinuo Zhou; Georgios Leontidis; Mingjun Zhong (Neural Comput. Appl., 2025)