**Fast Matrix Square Roots with Applications to Gaussian Processes and Bayesian Optimization[Paper]**

Geoff Pleiss, Martin Jankowiak, David Eriksson, Anil Damle, Jacob R. Gardner

Preprint (2020).

**Deep Sigma Point Processes[Paper]**

Martin Jankowiak, Geoff Pleiss, Jacob R. Gardner

Conference on Uncertainty in Artifical Intelligence (UAI 2020).

**Parametric Gaussian Process Regressors [Paper]**

Martin Jankowiak, Geoff Pleiss, Jacob R. Gardner

International Conference on Machine Learning (ICML 2020).

**Scalable Global Optimization via Local Bayesian Optimization [Paper]**

David Eriksson, Michael Pearce, Jacob R. Gardner, Ryan Turner, Matthias Poloczek

Neurial Information Processing Systems (NeurIPS 2019) **Spotlight.**

**Exact Gaussian Processes on a Million Data Points [Paper]**

Ke Alexander Wang, Geoff Pleiss, Jacob R. Gardner, Stephen Tyree, Kilian Q. Weinberger, Andrew G. Wilson

Neurial Information Processing Systems (NeurIPS 2019)

**Simple Blackbox Adversarial Attacks [Paper]**

Chuan Guo, Jacob R. Gardner, Yurong You, Andrew G. Wilson, Kilian Q. Weinberger

International Conference on Machine Learning (ICML 2019).

**GPyTorch: Blackbox Matrix-Matrix Gaussian Process Inference with GPU Acceleration [Paper]**

Jacob R. Gardner, Geoff Pleiss, Kilian Q. Weinberger, David Bindel, Andrew G. Wilson

Neurial Information Processing Systems (NeurIPS 2018). **Spotlight.**

**Constant Time Predictive Distributions for Gaussian Processes [Paper]**

Geoff Pleiss, Jacob R. Gardner, Kilian Q. Weinberger, Andrew G. Wilson

International Conference on Machine Learning (ICML 2018).

**Product Kernel Interpolation for Scalable Gaussian Processes [Paper]**

Jacob R. Gardner, Geoff Pleiss, Ruihan Wu, Kilian Q. Weinberger, Andrew G. Wilson

Artificial Intelligence and Statistics (AISTATS 2018)

**Discovering and Exploiting Additive Structure for Bayesian Optimization [Paper]**

Jacob R. Gardner, Chuan Guo, Kilian Q. Weinberger, Roman Garnett, Roger Grosse

Artificial Intelligence and Statistics (AISTATS 2017)

**Bayesian Active Model Selection with an Application to Automated Audiometry [Paper]**

Jacob R. Gardner, Gustavo Malkomes, Roman Garnett, Kilian Q. Weinberger, Dennis Barbour, John P. Cunningham

Neural Information Processing Systems (NeurIPS 2015)

**Psychophysical Detection Testing with Bayesian Active Learning [Paper]**

Jacob R. Gardner, Xinyu Song, Kilian Q. Weinberger, Dennis Barbour, John P. Cunningham

Uncertainty in Artifical Intelligence (UAI 2015)

**Deep feature interpolation for image content changes [Paper]**

Paul Upchurch*, Jacob R. Gardner*, Kavita Bala, Robert Pless, Noah Snavely, Kilian Q. Weinberger

Computer Vision and Pattern Recognition (CVPR 2016)

* authors contributed equally

**Deep manifold traversal: Changing labels with convolutional features [Paper]**

Jacob R. Gardner*, Paul Upchurch*, Matt J. Kusner, Yixuan Li, Kilian Q. Weinberger, Kavita Bala, John E. Hopcroft

* authors contributed equally

**Differentially Private Bayesian Optimization [Paper]**

Matthew J. Kusner, Jacob R. Gardner, Roman Garnett, Kilian Q. Weinberger

International Conference on Machine Learning (ICML 2015)

**A Reduction of the Elastic Net to Support Vector Machines with an Application to GPU Computing. [Paper]**

Quan Zhou, Wenlin Chen, Shiji Song, Jacob R. Gardner, Kilian Q. Weinberger, Yixin Chen

Association for the Advancement of Artificial Intelligence (AAAI 2015)

**Bayesian Optimization with Inequality Constraints. [Paper]**

Jacob R. Gardner, Matt J. Kusner, Zhixiang Xu, Kilian Q. Weinberger, John P. Cunningham

International Conference on Machine Learning (ICML 2014)