Jacob Gardner

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Kilian WeinbergerCornell UniversityDirección de correo verificada de cornell.edu
Geoff PleissAssistant Professor, University of British ColumbiaDirección de correo verificada de stat.ubc.ca
Andrew Gordon WilsonNew York UniversityDirección de correo verificada de cims.nyu.edu
John CunninghamProfessor, Columbia UniversityDirección de correo verificada de columbia.edu
David BindelProfessor of Computer Science, Cornell UniversityDirección de correo verificada de cs.cornell.edu
David ErikssonResearch Scientist Manager at MetaDirección de correo verificada de fb.com
Matt J. KusnerUniversity College LondonDirección de correo verificada de ucl.ac.uk
Dennis. L BarbourProfessor of Biomedical EngineeringDirección de correo verificada de opayq.com
Roman GarnettWashington University in St. LouisDirección de correo verificada de wustl.edu
Chuan GuoResearch Scientist, FAIR, MetaDirección de correo verificada de fb.com
Martin JankowiakGenerate BiomedicinesDirección de correo verificada de generatebiomedicines.com
Zhixiang (Eddie) XuWashington UniversityDirección de correo verificada de cse.wustl.edu
Stephen TyreeNVIDIADirección de correo verificada de nvidia.com
Paul UpchurchAppleDirección de correo verificada de cs.cornell.edu
Kavita BalaCornell UniversityDirección de correo verificada de cs.cornell.edu
Yurong YouNVIDIA ResearchDirección de correo verificada de nvidia.com
Xinyu D. SongWashington University in St. LouisDirección de correo verificada de wustl.edu
Noah SnavelyProfessor at Cornell Tech and Researcher at Google DeepMindDirección de correo verificada de cs.cornell.edu
Robert PlessGeorge Washington UniversityDirección de correo verificada de gwu.edu
Ke Alexander WangCS PhD student, Stanford UniversityDirección de correo verificada de cs.stanford.edu

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Jacob Gardner

University of Pennsylvania

Dirección de correo verificada de seas.upenn.edu - Página principal

Machine Learning Bayesian optimization Gaussian processes AI4Science


Título Ordenar por citas Ordenar por año Ordenar por título	Citado por Citado por	Año
Gpytorch: Blackbox matrix-matrix gaussian process inference with gpu acceleration JR Gardner, G Pleiss, D Bindel, KQ Weinberger, AG Wilson Advances in Neural Information Processing Systems, 2018	1422	2018
Simple black-box adversarial attacks C Guo, JR Gardner, Y You, AG Wilson, KQ Weinberger International Conference on Machine Learning, 2019	685	2019
Bayesian Optimization with Inequality Constraints. JR Gardner, MJ Kusner, ZE Xu, KQ Weinberger, JP Cunningham ICML 2014, 937-945, 2014	635	2014
Scalable global optimization via local bayesian optimization D Eriksson, M Pearce, JR Gardner, R Turner, M Poloczek Advances in Neural Information Processing Systems, 2019	582	2019
Deep feature interpolation for image content changes P Upchurch, J Gardner, G Pleiss, R Pless, N Snavely, K Bala, ... Proceedings of the IEEE conference on computer vision and pattern …, 2017	377	2017
Exact Gaussian processes on a million data points KA Wang, G Pleiss, JR Gardner, S Tyree, KQ Weinberger, AG Wilson Advances in Neural Information Processing Systems, 2019	290	2019
Constant-time predictive distributions for Gaussian processes G Pleiss, JR Gardner, KQ Weinberger, AG Wilson International Conference on Machine Learning, 2018	132	2018
Discovering and exploiting additive structure for Bayesian optimization J Gardner, C Guo, K Weinberger, R Garnett, R Grosse Artificial Intelligence and Statistics, 1311-1319, 2017	132	2017
Adversarial prompting for black box foundation models N Maus, P Chao, E Wong, J Gardner arXiv preprint arXiv:2302.04237 1 (2), 2023	101*	2023
Learning performance-improving code edits A Shypula, A Madaan, Y Zeng, U Alon, J Gardner, M Hashemi, G Neubig, ... International Conference on Learning Representations, 2024	98	2024
Parametric Gaussian Process Regressors M Jankowiak, G Pleiss, JR Gardner International Conference on Machine Learning, 2020	97	2020
Deep manifold traversal: Changing labels with convolutional features JR Gardner, P Upchurch, MJ Kusner, Y Li, KQ Weinberger, K Bala, ... arXiv preprint arXiv:1511.06421, 2015	91	2015
Product kernel interpolation for scalable Gaussian processes JR Gardner, G Pleiss, R Wu, KQ Weinberger, AG Wilson Artificial Intelligence and Statistics, 2018	89	2018
Local Latent Space Bayesian Optimization over Structured Inputs N Maus, HT Jones, JS Moore, MJ Kusner, J Bradshaw, JR Gardner Advances in Neural Information Processing Systems, 2022	78	2022
Fast, continuous audiogram estimation using machine learning XD Song, BM Wallace, JR Gardner, NM Ledbetter, KQ Weinberger, ... Ear and hearing 36 (6), e326-e335, 2015	73	2015
Differentially private Bayesian optimization M Kusner, J Gardner, R Garnett, K Weinberger International conference on machine learning, 918-927, 2015	69	2015
A reduction of the elastic net to support vector machines with an application to GPU computing Q Zhou, W Chen, S Song, J Gardner, K Weinberger, Y Chen Proceedings of the AAAI conference on artificial intelligence 29 (1), 2015	63	2015
Efficient Nonmyopic Bayesian Optimization via One-Shot Multi-Step Trees S Jiang, DR Jiang, M Balandat, B Karrer, JR Gardner, R Garnett Advances in Neural Information Processing Systems, 2020	59	2020
Fast matrix square roots with applications to Gaussian processes and Bayesian optimization G Pleiss, M Jankowiak, D Eriksson, A Damle, JR Gardner Advances in Neural Information Processing Systems, 2020	59	2020
Bayesian active model selection with an application to automated audiometry J Gardner, G Malkomes, R Garnett, KQ Weinberger, D Barbour, ... Advances in neural information processing systems 28, 2015	54	2015

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