Mingjun Zhong

CoRR, 2024

Masked Capsule Autoencoders.

[BibT_eX]

[DOI]

Miles Everett

CoRR, 2024

2023

Lightweight deep learning methods for panoramic dental X-ray image segmentation.

[BibT_eX]

[DOI]

Neural Comput. Appl., April, 2023

Nonintrusive Load Monitoring Based on Self-Supervised Learning.

[BibT_eX]

[DOI]

IEEE Trans. Instrum. Meas., 2023

ProtoCaps: A Fast and Non-Iterative Capsule Network Routing Method.

[BibT_eX]

[DOI]

Miles Everett

CoRR, 2023

Semantic Positive Pairs for Enhancing Contrastive Instance Discrimination.

[BibT_eX]

[DOI]

Mohammad Alkhalefi

CoRR, 2023

Vanishing Activations: A Symptom of Deep Capsule Networks.

[BibT_eX]

[DOI]

Miles Everett

CoRR, 2023

2022

System operational reliability evaluation based on dynamic Bayesian network and XGBoost.

[BibT_eX]

[DOI]

Reliab. Eng. Syst. Saf., 2022

Algorithms to Calculate the Most Reliable Maximum Flow in Content Delivery Network.

[BibT_eX]

[DOI]

Comput. Syst. Sci. Eng., 2022

LightNILM: lightweight neural network methods for non-intrusive load monitoring.

[BibT_eX]

[DOI]

Proceedings of the 9th ACM International Conference on Systems for Energy-Efficient Buildings, 2022

A Semantic Representation Scheme for Medical Dispute Judgment Documents Based on Elements Extraction.

[BibT_eX]

[DOI]

Proceedings of the Artificial Intelligence and Security - 8th International Conference, 2022

Causal Effect Estimation Using Variational Information Bottleneck.

[BibT_eX]

[DOI]

Proceedings of the Web Information Systems and Applications, 2022

2021

A discrete-time Bayesian network approach for reliability analysis of dynamic systems with common cause failures.

[BibT_eX]

[DOI]

Reliab. Eng. Syst. Saf., 2021

A Top-K QoS-Optimal Service Composition Approach Based on Service Dependency Graph.

[BibT_eX]

[DOI]

J. Organ. End User Comput., 2021

2020

Transfer Learning for Non-Intrusive Load Monitoring.

[BibT_eX]

[DOI]

Michele D'Incecco

Stefano Squartini

IEEE Trans. Smart Grid, 2020

Trust-Region Variational Inference with Gaussian Mixture Models.

[BibT_eX]

[DOI]

Oleg Arenz

Gerhard Neumann

J. Mach. Learn. Res., 2020

AREA: An adaptive reference-set based evolutionary algorithm for multiobjective optimisation.

[BibT_eX]

[DOI]

Inf. Sci., 2020

Lightweight Non-Intrusive Load Monitoring Employing Pruned Sequence-to-Point Learning.

[BibT_eX]

[DOI]

Proceedings of the NILM '20, 2020

2019

AREA: Adaptive Reference-set Based Evolutionary Algorithm for Multiobjective Optimisation.

[BibT_eX]

[DOI]

CoRR, 2019

A demonstration of reproducible state-of-the-art energy disaggregation using NILMTK.

[BibT_eX]

[DOI]

Proceedings of the 6th ACM International Conference on Systems for Energy-Efficient Buildings, 2019

Towards reproducible state-of-the-art energy disaggregation.

[BibT_eX]

[DOI]

Proceedings of the 6th ACM International Conference on Systems for Energy-Efficient Buildings, 2019

Neural Control Variates for Monte Carlo Variance Reduction.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2019

2018

A Hyperplane Clustering Algorithm for Estimating the Mixing Matrix in Sparse Component Analysis.

[BibT_eX]

[DOI]

Xu Xu

Chonghui Guo

Neural Process. Lett., 2018

Neural Control Variates for Variance Reduction.

[BibT_eX]

[DOI]

Zhanxing Zhu

Ruosi Wan

CoRR, 2018

Efficient Gradient-Free Variational Inference using Policy Search.

[BibT_eX]

[DOI]

Oleg Arenz

Gerhard Neumann

Proceedings of the 35th International Conference on Machine Learning, 2018

Sequence-to-Point Learning With Neural Networks for Non-Intrusive Load Monitoring.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017

Pseudo-marginal Markov Chain Monte Carlo for Nonnegative Matrix Factorization.

[BibT_eX]

[DOI]

Junfu Du

Neural Process. Lett., 2017

2016

Sequence-to-point learning with neural networks for nonintrusive load monitoring.

[BibT_eX]

[DOI]

CoRR, 2016

Classification of Normal/Abnormal Heart Sound Recordings based on Multi-Domain Features and Back Propagation Neural Network.

[BibT_eX]

[DOI]

Proceedings of the Computing in Cardiology, CinC 2016, Vancouver, 2016

2015

Latent Bayesian melding for integrating individual and population models.

[BibT_eX]

[DOI]

Nigel H. Goddard

Charles Sutton

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

2014

Signal Aggregate Constraints in Additive Factorial HMMs, with Application to Energy Disaggregation.

[BibT_eX]

[DOI]

Nigel H. Goddard

Charles Sutton

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

2013

A comparative evaluation of stochastic-based inference methods for Gaussian process models.

[BibT_eX]

[DOI]

Maurizio Filippone

Mach. Learn., 2013

2012

Bayesian Analysis for miRNA and mRNA Interactions Using Expression Data

[BibT_eX]

[DOI]

Rong Liu

Bo Liu

CoRR, 2012

A Bayesian Approach to Approximate Joint Diagonalization of Square Matrices.

[BibT_eX]

[DOI]

Proceedings of the 29th International Conference on Machine Learning, 2012

2009

Reversible Jump MCMC for Non-Negative Matrix Factorization.

[BibT_eX]

[DOI]

Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, 2009

2008

Classifying EEG for brain computer interfaces using Gaussian processes.

[BibT_eX]

[DOI]

Pattern Recognit. Lett., 2008

Scale-free network model under exogenous pressures.

[BibT_eX]

[DOI]

Qiang Guo

Jian-Guo Liu

Int. J. Model. Identif. Control., 2008

2007

A parametric density model for blind source separation.

[BibT_eX]

[DOI]

Junfu Du

Neural Process. Lett., 2007

2006

A variational method for learning sparse Bayesian regression.

[BibT_eX]

[DOI]

Neurocomputing, 2006

Data Integration for Classification Problems Employing Gaussian Process Priors.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 19, 2006

2004

Expectation-Maximization approaches to independent component analysis.

[BibT_eX]

[DOI]