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Kuilin Chen
Kuilin Chen
Verified email at mail.utoronto.ca
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Cited by
Year
Short-term wind speed prediction using an unscented Kalman filter based state-space support vector regression approach
K Chen, J Yu
Applied energy 113, 690-705, 2014
3222014
A Gaussian mixture copula model based localized Gaussian process regression approach for long-term wind speed prediction
J Yu, K Chen, J Mori, MM Rashid
Energy 61, 673-686, 2013
732013
Incremental few-shot learning via vector quantization in deep embedded space
K Chen, CG Lee
International Conference on Learning Representations, 2020
712020
A Bayesian model averaging based multi-kernel Gaussian process regression framework for nonlinear state estimation and quality prediction of multiphase batch processes with …
J Yu, K Chen, MM Rashid
Chemical Engineering Science 93, 96-109, 2013
542013
Soft sensor model maintenance: A case study in industrial processes
K Chen, I Castillo, LH Chiang, J Yu
IFAC-PapersOnLine 48 (8), 427-432, 2015
322015
Unsupervised few-shot learning via deep laplacian eigenmaps
K Chen, CG Lee
arXiv preprint arXiv:2210.03595, 2022
32022
Meta-free few-shot learning via representation learning with weight averaging
K Chen, CG Lee
2022 International Joint Conference on Neural Networks (IJCNN), 1-8, 2022
32022
Attentive Gaussian processes for probabilistic time-series generation
K Chen, CG Lee
Canadian Operational Research Society Conference, 2021
22021
Multi-kernel Gaussian process regression and Bayesian model averaging based nonlinear state estimation and quality prediction of multiphase batch processes
J Yu, K Chen, J Mori, MM Rashid
2013 American Control Conference, 5451-5456, 2013
22013
Adversarial perturbation based latent reconstruction for domain-agnostic self-supervised learning
K Chen, S Tian, CG Lee
NeurIPS 2023 Workshop: Self-Supervised Learning - Theory and Practice, 2022
12022
Learning Representation to Build Models with Few-shot Data
K Chen
University of Toronto, 2022
2022
Data-driven modeling for quality control in chemical processes
K Chen
McMaster University, 2014
2014
Expectation-maximization and Bayesian inference based probabilistic PLS methods for soft sensor estimation and prediction of industrial processes with stochastic missing …
K Chen, J Yu, I Castillo, LH Chiang
2013 AIChE Annual Meeting, 2013
2013
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Articles 1–13