Zhong, Mingjun

15 publications

TMLR 2025 Capsule Network Projectors Are Equivariant and Invariant Learners Miles Everett, Aiden Durrant, Mingjun Zhong, Georgios Leontidis

TMLR 2025 Masked Capsule Autoencoders Miles Everett, Mingjun Zhong, Georgios Leontidis

TMLR 2024 LeOCLR: Leveraging Original Images for Contrastive Learning of Visual Representations Mohammad Alkhalefi, Georgios Leontidis, Mingjun Zhong

TMLR 2024 Semantic Positive Pairs for Enhancing Visual Representation Learning of Instance Discrimination Methods Mohammad Alkhalefi, Georgios Leontidis, Mingjun Zhong

TMLR 2023 ProtoCaps: A Fast and Non-Iterative Capsule Network Routing Method Miles Everett, Mingjun Zhong, Georgios Leontidis

JMLR 2020 Trust-Region Variational Inference with Gaussian Mixture Models Oleg Arenz, Mingjun Zhong, Gerhard Neumann

ECML-PKDD 2019 Neural Control Variates for Monte Carlo Variance Reduction Ruosi Wan, Mingjun Zhong, Haoyi Xiong, Zhanxing Zhu

ICML 2018 Efficient Gradient-Free Variational Inference Using Policy Search Oleg Arenz, Gerhard Neumann, Mingjun Zhong

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

NeurIPS 2015 Latent Bayesian Melding for Integrating Individual and Population Models Mingjun Zhong, Nigel Goddard, Charles Sutton

NeurIPS 2014 Signal Aggregate Constraints in Additive Factorial HMMs, with Application to Energy Disaggregation Mingjun Zhong, Nigel Goddard, Charles Sutton

MLJ 2013 A Comparative Evaluation of Stochastic-Based Inference Methods for Gaussian Process Models Maurizio Filippone, Mingjun Zhong, Mark A. Girolami

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

AISTATS 2009 Reversible Jump MCMC for Non-Negative Matrix Factorization Mingjun Zhong, Mark Girolami

NeurIPS 2006 Data Integration for Classification Problems Employing Gaussian Process Priors Mark Girolami, Mingjun Zhong