Haitao Liu

Orcid: 0000-0003-1187-5374

Affiliations:
  • Dalian University of Technology, School of Energy and Power Engineering, Dalian, China


According to our database1, Haitao Liu authored at least 23 papers between 2015 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2024
A parallel and multi-scale probabilistic temporal convolutional neural networks for forecasting the key monitoring parameters of gas turbine.
Eng. Appl. Artif. Intell., 2024

Transfer condition assessment of gas turbines via double multi-task Gaussian process.
Adv. Eng. Informatics, 2024

An efficient mixed constrained Bayesian optimization for handling known and unknown constraints.
Adv. Eng. Informatics, 2024

2023
Learning Multitask Gaussian Process Over Heterogeneous Input Domains.
IEEE Trans. Syst. Man Cybern. Syst., October, 2023

Choose Appropriate Subproblems for Collaborative Modeling in Expensive Multiobjective Optimization.
IEEE Trans. Cybern., 2023

Generative Multiform Bayesian Optimization.
IEEE Trans. Cybern., 2023

2022
Scalable Gaussian Process Classification With Additive Noise for Non-Gaussian Likelihoods.
IEEE Trans. Cybern., 2022

Deep Latent-Variable Kernel Learning.
IEEE Trans. Cybern., 2022

Co-Learning Bayesian Optimization.
IEEE Trans. Cybern., 2022

Scalable multi-task Gaussian processes with neural embedding of coregionalization.
Knowl. Based Syst., 2022

Learning Multi-Task Gaussian Process Over Heterogeneous Input Domains.
CoRR, 2022

2021
Large-Scale Heteroscedastic Regression via Gaussian Process.
IEEE Trans. Neural Networks Learn. Syst., 2021

Modulating scalable Gaussian processes for expressive statistical learning.
Pattern Recognit., 2021

Deep Probabilistic Time Series Forecasting using Augmented Recurrent Input for Dynamic Systems.
CoRR, 2021

2020
When Gaussian Process Meets Big Data: A Review of Scalable GPs.
IEEE Trans. Neural Networks Learn. Syst., 2020

2019
Understanding and comparing scalable Gaussian process regression for big data.
Knowl. Based Syst., 2019

Fast transfer Gaussian process regression with large-scale sources.
Knowl. Based Syst., 2019

Scalable Gaussian Process Classification with Additive Noise for Various Likelihoods.
CoRR, 2019

2018
Remarks on multi-output Gaussian process regression.
Knowl. Based Syst., 2018

Cope with diverse data structures in multi-fidelity modeling: A Gaussian process method.
Eng. Appl. Artif. Intell., 2018

Generalized Robust Bayesian Committee Machine for Large-scale Gaussian Process Regression.
Proceedings of the 35th International Conference on Machine Learning, 2018

2017
An adaptive sampling approach for Kriging metamodeling by maximizing expected prediction error.
Comput. Chem. Eng., 2017

2015
Global optimization of expensive black box functions using potential Lipschitz constants and response surfaces.
J. Glob. Optim., 2015


  Loading...