Zhenwen Dai
Zhenwen Dai
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TitleCited byYear
Batch Bayesian Optimization via Local Penalization
J González, Z Dai, P Hennig, ND Lawrence
International Conference on Artificial Intelligence and Statistics, 2015
1112015
Variational Auto-encoded Deep Gaussian Processes
Z Dai, A Damianou, J González, N Lawrence
International Conference on Learning Representations (ICLR), 2015
862015
Recurrent Gaussian Processes
CLC Mattos, Z Dai, A Damianou, J Forth, GA Barreto, ND Lawrence
International Conference on Learning Representations (ICLR), 2015
432015
Gaussian process models with parallelization and GPU acceleration
Z Dai, A Damianou, J Hensman, N Lawrence
arXiv preprint arXiv:1410.4984, 2014
252014
GPy: A Gaussian process framework in python
GPy
https://github.com/SheffieldML/GPy, 2012
19*2012
Autonomous Document Cleaning—A Generative Approach to Reconstruct Strongly Corrupted Scanned Texts
Z Dai, J Lucke
IEEE Transactions on Pattern Analysis and Machine Intelligence 36 (10), 1950 …, 2014
172014
Polygonal light source estimation
D Schnieders, KYK Wong, Z Dai
Asian conference on computer vision, 96-107, 2009
162009
Efficient Modeling of Latent Information in Supervised Learning using Gaussian Processes
Z Dai, MA Álvarez, ND Lawrence
Advances in Neural Information Processing Systems, 2017
152017
Auto-differentiating linear algebra
M Seeger, A Hetzel, Z Dai, E Meissner, ND Lawrence
arXiv preprint arXiv:1710.08717, 2017
132017
GP-select: Accelerating EM using adaptive subspace preselection
JA Shelton, J Gasthaus, Z Dai, J Lücke, A Gretton
Neural Computation 29 (8), 2177-2202, 2017
132017
What are the invariant occlusive components of image patches? A probabilistic generative approach
Z Dai, G Exarchakis, J Lücke
Advances in neural information processing systems, 243-251, 2013
132013
Understanding research field evolving and trend with dynamic Bayesian networks
J Wang, C Xu, G Li, Z Dai, G Luo
Pacific-Asia Conference on Knowledge Discovery and Data Mining, 320-331, 2007
132007
Variational Information Distillation for Knowledge Transfer
S Ahn, SX Hu, A Damianou, ND Lawrence, Z Dai
IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2019
122019
Unsupervised learning of translation invariant occlusive components
Z Dai, J Lücke
2012 IEEE Conference on Computer Vision and Pattern Recognition, 2400-2407, 2012
122012
Preferential Bayesian Optimization
J Gonzalez, Z Dai, A Damianou, ND Lawrence
International Conference on Machine Learning, 2017
112017
GPyOpt: a Bayesian optimization framework in Python
J González
112016
Deep recurrent Gaussian processes for outlier-robust system identification
CLC Mattos, Z Dai, A Damianou, GA Barreto, ND Lawrence
Journal of Process Control 60, 82-94, 2017
102017
Pose estimation from reflections for specular surface recovery
M Liu, KYK Wong, Z Dai, Z Chen
2011 International Conference on Computer Vision, 579-586, 2011
102011
Specular surface recovery from reflections of a planar pattern undergoing an unknown pure translation
M Liu, KYK Wong, Z Dai, Z Chen
Asian Conference on Computer Vision, 137-147, 2010
102010
Structured variationally auto-encoded optimization
X Lu, J Gonzalez, Z Dai, N Lawrence
International Conference on Machine Learning, 3267-3275, 2018
82018
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