Mingjun Zhong - RankMe

60 papers A* 4A 1Misc 1Journal 44Unranked 10

Year	Rank	Type	Title / Venue / Authors
2026	A*	`conf`	DSCF: Dual-Source Counterfactual Fusion for High-Dimensional Combinatorial Interventions. AAAI Jitong Dou, Lingrui Luo, Bing Zhu, Hengliang Luo, Mingjun Zhong, Yurong Cheng
2025	J	`jnl`	Capsule Network Projectors are Equivariant and Invariant Learners. Trans. Mach. Learn. Res. Miles Everett, Aiden Durrant, Mingjun Zhong, Georgios Leontidis
2025	J	`jnl`	Enhancing Self-Supervised Learning with Semantic Pairs A New Dataset and Empirical Study. CoRR Mohammad Alkhalefi, Georgios Leontidis, Mingjun Zhong
2025	J	`jnl`	FlowETL: An Autonomous Example-Driven Pipeline for Data Engineering. CoRR Mattia Di Profio, Mingjun Zhong, Yaji Sripada, Marcel Jaspars
2025	J	`jnl`	Masked Capsule Autoencoders. Trans. Mach. Learn. Res. Miles Everett, Mingjun Zhong, Georgios Leontidis
2025	J	`jnl`	Multisource Domain Adaptation for Nonintrusive Load Monitoring Through Data Distillation. IEEE Trans. Instrum. Meas. Wenpeng Luan, Ruiqi Zhang, Bo Liu, Mingjun Zhong, Keke Li
2025	J	`jnl`	OmniNet: an expandable causal inference network for multiple modalities. Neural Comput. Appl. Yinuo Zhou, Georgios Leontidis, Mingjun Zhong
2024	J	`jnl`	A Survey of Pipeline Tools for Data Engineering. CoRR Anthony Mbata, Yaji Sripada, Mingjun Zhong
2024	J	`jnl`	Capsule Network Projectors are Equivariant and Invariant Learners. CoRR Miles Everett, Aiden Durrant, Mingjun Zhong, Georgios Leontidis
2024	J	`jnl`	LeOCLR: Leveraging Original Images for Contrastive Learning of Visual Representations. CoRR Mohammad Alkhalefi, Georgios Leontidis, Mingjun Zhong
2024	J	`jnl`	LeOCLR: Leveraging Original Images for Contrastive Learning of Visual Representations. Trans. Mach. Learn. Res. Mohammad Alkhalefi, Georgios Leontidis, Mingjun Zhong
2024	J	`jnl`	Masked Capsule Autoencoders. CoRR Miles Everett, Mingjun Zhong, Georgios Leontidis
2024	J	`jnl`	Semantic Positive Pairs for Enhancing Visual Representation Learning of Instance Discrimination methods. Trans. Mach. Learn. Res. Mohammad Alkhalefi, Georgios Leontidis, Mingjun Zhong
2023	J	`jnl`	Lightweight deep learning methods for panoramic dental X-ray image segmentation. Neural Comput. Appl. Songyue Lin, Xuejiang Hao, Yan Liu, Dong Yan, Jianwei Liu, Mingjun Zhong
2023	J	`jnl`	Nonintrusive Load Monitoring Based on Self-Supervised Learning. IEEE Trans. Instrum. Meas. Shuyi Chen, Bochao Zhao, Mingjun Zhong, Wenpeng Luan, Yixin Yu
2023	J	`jnl`	ProtoCaps: A Fast and Non-Iterative Capsule Network Routing Method. CoRR Miles Everett, Mingjun Zhong, Georgios Leontidis
2023	J	`jnl`	ProtoCaps: A Fast and Non-Iterative Capsule Network Routing Method. Trans. Mach. Learn. Res. Miles Everett, Mingjun Zhong, Georgios Leontidis
2023	J	`jnl`	Semantic Positive Pairs for Enhancing Contrastive Instance Discrimination. CoRR Mohammad Alkhalefi, Georgios Leontidis, Mingjun Zhong
2023	J	`jnl`	Vanishing Activations: A Symptom of Deep Capsule Networks. CoRR Miles Everett, Mingjun Zhong, Georgios Leontidis
2022	—	`conf`	A Semantic Representation Scheme for Medical Dispute Judgment Documents Based on Elements Extraction. ICAIS (2) Siyao An, Tianhao Wang, Lirui Wang, Mingjun Zhong, Baili Zhang
2022	J	`jnl`	Algorithms to Calculate the Most Reliable Maximum Flow in Content Delivery Network. Comput. Syst. Sci. Eng. Baili Zhang, Keke Ling, Pei Zhang, Zhao Zhang, Mingjun Zhong
2022	Misc	`conf`	Causal Effect Estimation Using Variational Information Bottleneck. WISA Zhenyu Lu, Yurong Cheng, Mingjun Zhong, George Stoian, Ye Yuan, Guoren Wang
2022	—	`conf`	LightNILM: lightweight neural network methods for non-intrusive load monitoring. BuildSys Zhenyu Lu, Yurong Cheng, Mingjun Zhong, Wenpeng Luan, Yuan Ye, Guoren Wang
2022	J	`jnl`	System operational reliability evaluation based on dynamic Bayesian network and XGBoost. Reliab. Eng. Syst. Saf. Yongjin Guo, Hongdong Wang, Yu Guo, Mingjun Zhong, Qing Li, Chao Gao
2021	J	`jnl`	A Top-K QoS-Optimal Service Composition Approach Based on Service Dependency Graph. J. Organ. End User Comput. Baili Zhang, Kejie Wen, Jianhua Lu, Mingjun Zhong
2021	J	`jnl`	A discrete-time Bayesian network approach for reliability analysis of dynamic systems with common cause failures. Reliab. Eng. Syst. Saf. Yongjin Guo, Mingjun Zhong, Chao Gao, Hong Dong Wang, Xiaofeng Liang, Hong Yi
2021	J	`jnl`	Causal Effect Estimation using Variational Information Bottleneck. CoRR Zhenyu Lu, Yurong Cheng, Mingjun Zhong, George Stoian, Ye Yuan, Guoren Wang
2020	J	`jnl`	AREA: An adaptive reference-set based evolutionary algorithm for multiobjective optimisation. Inf. Sci. Shouyong Jiang, Hongru Li, Jinglei Guo, Mingjun Zhong, Shengxiang Yang, Marcus Kaiser, Natalio Krasnogor
2020	—	`conf`	Lightweight Non-Intrusive Load Monitoring Employing Pruned Sequence-to-Point Learning. NILM@SenSys Jack Barber, Heriberto Cuayáhuitl, Mingjun Zhong, Wenpeng Luan
2020	J	`jnl`	Transfer Learning for Non-Intrusive Load Monitoring. IEEE Trans. Smart Grid Michele D'Incecco, Stefano Squartini, Mingjun Zhong
2020	J	`jnl`	Trust-Region Variational Inference with Gaussian Mixture Models. J. Mach. Learn. Res. Oleg Arenz, Mingjun Zhong, Gerhard Neumann
2019	—	`conf`	A demonstration of reproducible state-of-the-art energy disaggregation using NILMTK. BuildSys Nipun Batra, Rithwik Kukunuri, Ayush Pandey, Raktim Malakar, Rajat Kumar, Odysseas Krystalakos, Mingjun Zhong, Paulo Meira, Oliver Parson
2019	J	`jnl`	AREA: Adaptive Reference-set Based Evolutionary Algorithm for Multiobjective Optimisation. CoRR Shouyong Jiang, Hongru Li, Jinglei Guo, Mingjun Zhong, Shengxiang Yang, Marcus Kaiser, Natalio Krasnogor
2019	—	`conf`	Neural Control Variates for Monte Carlo Variance Reduction. ECML/PKDD (2) Ruosi Wan, Mingjun Zhong, Haoyi Xiong, Zhanxing Zhu
2019	—	`conf`	Towards reproducible state-of-the-art energy disaggregation. BuildSys Nipun Batra, Rithwik Kukunuri, Ayush Pandey, Raktim Malakar, Rajat Kumar, Odysseas Krystalakos, Mingjun Zhong, Paulo Meira, Oliver Parson
2019	J	`jnl`	Transfer Learning for Non-Intrusive Load Monitoring. CoRR Michele D'Incecco, Stefano Squartini, Mingjun Zhong
2019	J	`jnl`	Trust-Region Variational Inference with Gaussian Mixture Models. CoRR Oleg Arenz, Mingjun Zhong, Gerhard Neumann
2018	J	`jnl`	A Hyperplane Clustering Algorithm for Estimating the Mixing Matrix in Sparse Component Analysis. Neural Process. Lett. Xu Xu, Mingjun Zhong, Chonghui Guo
2018	J	`jnl`	Classification of normal/abnormal heart sound recordings based on multi-domain features and back propagation neural network. CoRR Hong Tang, Huaming Chen, Ting Li, Mingjun Zhong
2018	A*	`conf`	Efficient Gradient-Free Variational Inference using Policy Search. ICML Oleg Arenz, Mingjun Zhong, Gerhard Neumann
2018	J	`jnl`	Neural Control Variates for Variance Reduction. CoRR Zhanxing Zhu, Ruosi Wan, Mingjun Zhong
2018	A*	`conf`	Sequence-to-Point Learning With Neural Networks for Non-Intrusive Load Monitoring. AAAI Chaoyun Zhang, Mingjun Zhong, Zongzuo Wang, Nigel H. Goddard, Charles Sutton
2017	J	`jnl`	Pseudo-marginal Markov Chain Monte Carlo for Nonnegative Matrix Factorization. Neural Process. Lett. Junfu Du, Mingjun Zhong
2016	—	`conf`	Classification of Normal/Abnormal Heart Sound Recordings based on Multi-Domain Features and Back Propagation Neural Network. CinC Hong Tang, Huaming Chen, Ting Li, Mingjun Zhong
2016	J	`jnl`	Sequence-to-point learning with neural networks for nonintrusive load monitoring. CoRR Chaoyun Zhang, Mingjun Zhong, Zongzuo Wang, Nigel H. Goddard, Charles Sutton
2015	—	`conf`	Latent Bayesian melding for integrating individual and population models. NIPS Mingjun Zhong, Nigel H. Goddard, Charles Sutton
2015	J	`jnl`	Latent Bayesian melding for integrating individual and population models. CoRR Mingjun Zhong, Nigel H. Goddard, Charles Sutton
2014	—	`conf`	Signal Aggregate Constraints in Additive Factorial HMMs, with Application to Energy Disaggregation. NIPS Mingjun Zhong, Nigel H. Goddard, Charles Sutton
2013	J	`jnl`	A comparative evaluation of stochastic-based inference methods for Gaussian process models. Mach. Learn. Maurizio Filippone, Mingjun Zhong, Mark A. Girolami
2012	J	`jnl`	A Bayesian Approach to Approximate Joint Diagonalization of Square Matrices CoRR Mingjun Zhong, Mark A. Girolami
2012	A*	`conf`	A Bayesian Approach to Approximate Joint Diagonalization of Square Matrices. ICML Mingjun Zhong, Mark A. Girolami
2012	J	`jnl`	Bayesian Analysis for miRNA and mRNA Interactions Using Expression Data CoRR Mingjun Zhong, Rong Liu, Bo Liu
2009	A	`conf`	Reversible Jump MCMC for Non-Negative Matrix Factorization. AISTATS Mingjun Zhong, Mark A. Girolami
2008	J	`jnl`	Classifying EEG for brain computer interfaces using Gaussian processes. Pattern Recognit. Lett. Mingjun Zhong, Fabien Lotte, Mark A. Girolami, Anatole Lécuyer
2008	J	`jnl`	Scale-free network model under exogenous pressures. Int. J. Model. Identif. Control. Qiang Guo, Jian-Guo Liu, Mingjun Zhong
2007	J	`jnl`	A parametric density model for blind source separation. Neural Process. Lett. Mingjun Zhong, Junfu Du
2006	J	`jnl`	A variational method for learning sparse Bayesian regression. Neurocomputing Mingjun Zhong
2006	—	`conf`	Data Integration for Classification Problems Employing Gaussian Process Priors. NIPS Mark A. Girolami, Mingjun Zhong
2004	J	`jnl`	An EM algorithm for learning sparse and overcomplete representations. Neurocomputing Mingjun Zhong, Huanwen Tang, Hongjun Chen, Yiyuan Tang
2004	J	`jnl`	Expectation-Maximization approaches to independent component analysis. Neurocomputing Mingjun Zhong, Huanwen Tang, Yiyuan Tang