Zhenwen Dai - Google Scholar

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	All	Since 2015
Citations	706	658
h-index	14	13
i10-index	20	16

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Co-authors

Neil D. LawrenceUniversity of CambridgeVerified email at cl.cam.ac.uk
Andreas DamianouAmazon.comVerified email at amazon.com
Javier GonzálezMicrosoft Research CambridgeVerified email at microsoft.com
Jorg LuckeProfessor of Machine Learning, University of Oldenburg, Germany.Verified email at uni-oldenburg.de
Philipp HennigUniversity of Tübingen & Max Planck Institute for Intelligent SystemsVerified email at tue.mpg.de
Kwan-Yee Kenneth WongAssociate Professor of Computer Science, The University of Hong KongVerified email at cs.hku.hk
Guilherme A. BarretoDepartment of Teleinformatics Engineering, Federal University of CearáVerified email at ufc.br
César Lincoln Cavalcante MattosFederal University of Ceará (UFC)Verified email at dc.ufc.br
Eric MeissnerPhD Candidate, University of CambridgeVerified email at cam.ac.uk
Shell Xu HuUpload AI LLCVerified email at uploadai.com
Sungsoo AhnKAISTVerified email at kaist.ac.kr
James HensmanPrincipal scientist, AmazonVerified email at amazon.com
Georgios ExarchakisInstitut de la VisionVerified email at ens.fr
Jacquelyn A SheltonPhD Technical University BerlinVerified email at tu-berlin.de
Miaomiao LiuAustralian National UniversityVerified email at anu.edu.au
arthur grettonGatsby Computational Neuroscience Unit, UCLVerified email at gatsby.ucl.ac.uk
Jan GasthausGatsby Computational Neuroscience Unit, UCLVerified email at ucl.ac.uk
Jörg BornscheinDeepMindVerified email at google.com
Jose A. Rodriguez-SerranoData Science Program Manager at BBVA Data & AnalyticsVerified email at bbvadata.com
Mauricio A. ÁlvarezUniversity of SheffieldVerified email at sheffield.ac.uk

Zhenwen Dai

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machine learning computer vision


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Batch Bayesian Optimization via Local Penalization J González, Z Dai, P Hennig, ND Lawrence International Conference on Artificial Intelligence and Statistics, 2015	163	2015
Variational Auto-encoded Deep Gaussian Processes Z Dai, A Damianou, J González, N Lawrence International Conference on Learning Representations (ICLR), 2015	100	2015
Recurrent Gaussian Processes CLC Mattos, Z Dai, A Damianou, J Forth, GA Barreto, ND Lawrence International Conference on Learning Representations (ICLR), 2015	50	2015
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	40	2019
Gaussian process models with parallelization and GPU acceleration Z Dai, A Damianou, J Hensman, N Lawrence arXiv preprint arXiv:1410.4984, 2014	28	2014
Preferential Bayesian Optimization J Gonzalez, Z Dai, A Damianou, ND Lawrence International Conference on Machine Learning, 2017	27	2017
GPy: A Gaussian process framework in python GPy https://github.com/SheffieldML/GPy, 2012	24*	2012
Efficient Modeling of Latent Information in Supervised Learning using Gaussian Processes Z Dai, MA Álvarez, ND Lawrence Advances in Neural Information Processing Systems, 2017	20	2017
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	18	2014
Polygonal light source estimation D Schnieders, KYK Wong, Z Dai Asian conference on computer vision, 96-107, 2009	18	2009
Auto-differentiating linear algebra M Seeger, A Hetzel, Z Dai, E Meissner, ND Lawrence arXiv preprint arXiv:1710.08717, 2017	15	2017
GPyOpt: a Bayesian optimization framework in Python J González, Z Dai Accessed, 2016	15	2016
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	15	2013
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	14	2017
Structured variationally auto-encoded optimization X Lu, J Gonzalez, Z Dai, N Lawrence International Conference on Machine Learning, 3267-3275, 2018	13	2018
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	13	2017
Unsupervised learning of translation invariant occlusive components Z Dai, J Lücke 2012 IEEE Conference on Computer Vision and Pattern Recognition, 2400-2407, 2012	13	2012
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	13	2007
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	11	2011
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	10	2010

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