John P. Cunningham
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
22
Venues
5
Active years
2007–2022
Best venue rank
A*
Where they publish
Papers
22 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2022 | ICML | Scaling Structured Inference with Randomization. | Yao Fu, John P. Cunningham, Mirella Lapata |
| 2022 | ICML | Preconditioning for Scalable Gaussian Process Hyperparameter Optimization. | Jonathan Wenger, Geoff Pleiss, Philipp Hennig, John P. Cunningham, Jacob R. Gardner |
| 2022 | ICML | Variational nearest neighbor Gaussian process. | Luhuan Wu, Geoff Pleiss, John P. Cunningham |
| 2021 | AISTATS | Hierarchical Inducing Point Gaussian Process for Inter-domian Observations. | Luhuan Wu, Andrew Miller, Lauren Anderson, Geoff Pleiss, David M. Blei, John P. Cunningham |
| 2021 | ICML | Bias-Free Scalable Gaussian Processes via Randomized Truncations. | Andres Potapczynski, Luhuan Wu, Dan Biderman, Geoff Pleiss, John P. Cunningham |
| 2020 | ICML | The continuous categorical: a novel simplex-valued exponential family. | Elliott Gordon-Rodrguez, Gabriel Loaiza-Ganem, John P. Cunningham |
| 2019 | AISTATS | Calibrating Deep Convolutional Gaussian Processes. | Gia-Lac Tran, Edwin V. Bonilla, John P. Cunningham, Pietro Michiardi, Maurizio Filippone |
| 2019 | ICLR | Deep Random Splines for Point Process Intensity Estimation. | Gabriel Loaiza-Ganem, John P. Cunningham |
| 2019 | ICML | Discriminative Regularization for Latent Variable Models with Applications to Electrocardiography. | Andrew C. Miller, Ziad Obermeyer, John P. Cunningham, Sendhil Mullainathan |
| 2018 | AISTATS | Reparameterizing the Birkhoff Polytope for Variational Permutation Inference. | Scott W. Linderman, Gonzalo E. Mena, Hal James Cooper, Liam Paninski, John P. Cunningham |
| 2017 | AISTATS | Annular Augmentation Sampling. | Francois Fagan, Jalaj Bhandari, John P. Cunningham |
| 2017 | ICLR | Maximum Entropy Flow Networks. | Gabriel Loaiza-Ganem, Yuanjun Gao, John P. Cunningham |
| 2016 | ICML | Slice Sampling on Hamiltonian Trajectories. | Benjamin Bloem-Reddy, John P. Cunningham |
| 2016 | ICML | Preconditioning Kernel Matrices. | Kurt Cutajar, Michael A. Osborne, John P. Cunningham, Maurizio Filippone |
| 2016 | UAI | Elliptical Slice Sampling with Expectation Propagation. | Francois Fagan, Jalaj Bhandari, John P. Cunningham |
| 2016 | UAI | Bayesian Learning of Kernel Embeddings. | Seth R. Flaxman, Dino Sejdinovic, John P. Cunningham, Sarah Filippi |
| 2015 | UAI | Psychophysical Detection Testing with Bayesian Active Learning. | Jacob R. Gardner, Xinyu Song, Kilian Q. Weinberger, Dennis L. Barbour, John P. Cunningham |
| 2014 | ICML | Bayesian Optimization with Inequality Constraints. | Jacob R. Gardner, Matt J. Kusner, Zhixiang Eddie Xu, Kilian Q. Weinberger, John P. Cunningham |
| 2013 | ICML | Scaling Multidimensional Gaussian Processes using Projected Additive Approximations. | Elad Gilboa, Yunus Saati, John P. Cunningham |
| 2009 | ICML | Workshop summary: Numerical mathematics in machine learning. | Matthias W. Seeger, Suvrit Sra, John P. Cunningham |
| 2008 | ICML | Fast Gaussian process methods for point process intensity estimation. | John P. Cunningham, Krishna V. Shenoy, Maneesh Sahani |
| 2007 | ICONIP | Neural Decoding of Movements: From Linear to Nonlinear Trajectory Models. | Byron M. Yu, John P. Cunningham, Krishna V. Shenoy, Maneesh Sahani |