131 citations · 197 across the 9 of their papers we have counts for
10 papers
Vanishing Activations: A Symptom of Deep Capsule Networks
Miles Everett, Mingjun Zhong, Georgios Leontidis
Capsule Networks, an extension to Neural Networks utilizing vector or matrix representations instead of scalars, were initially developed to create a dynamic parse tree where visua…
Causal Effect Estimation using Variational Information Bottleneck
Zhenyu Lu, Yurong Cheng, Mingjun Zhong +3
Causal inference is to estimate the causal effect in a causal relationship when intervention is applied. Precisely, in a causal model with binary interventions, i.e., control and t…
Trust-Region Variational Inference with Gaussian Mixture Models
Oleg Arenz, Mingjun Zhong, Gerhard Neumann
Many methods for machine learning rely on approximate inference from intractable probability distributions. Variational inference approximates such distributions by tractable model…
Classification of normal/abnormal heart sound recordings based on multi-domain features and back propagation neural network
Hong Tang, Huaming Chen, Ting Li +1
This paper aims to classify a single PCG recording as normal or abnormal for computer-aided diagnosis. The proposed framework for this challenge has four steps: preprocessing, feat…
Neural Control Variates for Variance Reduction
Ruosi Wan, Mingjun Zhong, Haoyi Xiong +1
In statistics and machine learning, approximation of an intractable integration is often achieved by using the unbiased Monte Carlo estimator, but the variances of the estimation a…
Sequence-to-point learning with neural networks for nonintrusive load monitoring
Chaoyun Zhang, Mingjun Zhong, Zongzuo Wang +2
Energy disaggregation (a.k.a nonintrusive load monitoring, NILM), a single-channel blind source separation problem, aims to decompose the mains which records the whole house electr…