Get our free extension to see links to code for papers anywhere online!

Chrome logo Add to Chrome

Firefox logo Add to Firefox

Picture for Jasper Snoek

Sparse MoEs meet Efficient Ensembles


Oct 07, 2021
James Urquhart Allingham, Florian Wenzel, Zelda E Mariet, Basil Mustafa, Joan Puigcerver, Neil Houlsby, Ghassen Jerfel, Vincent Fortuin, Balaji Lakshminarayanan, Jasper Snoek, Dustin Tran, Carlos Riquelme Ruiz, Rodolphe Jenatton

* 44 pages, 19 figures, 24 tables 

  Access Paper or Ask Questions

Automatic prior selection for meta Bayesian optimization with a case study on tuning deep neural network optimizers


Sep 16, 2021
Zi Wang, George E. Dahl, Kevin Swersky, Chansoo Lee, Zelda Mariet, Zack Nado, Justin Gilmer, Jasper Snoek, Zoubin Ghahramani


  Access Paper or Ask Questions

Uncertainty Baselines: Benchmarks for Uncertainty & Robustness in Deep Learning


Jun 07, 2021
Zachary Nado, Neil Band, Mark Collier, Josip Djolonga, Michael W. Dusenberry, Sebastian Farquhar, Angelos Filos, Marton Havasi, Rodolphe Jenatton, Ghassen Jerfel, Jeremiah Liu, Zelda Mariet, Jeremy Nixon, Shreyas Padhy, Jie Ren, Tim G. J. Rudner, Yeming Wen, Florian Wenzel, Kevin Murphy, D. Sculley, Balaji Lakshminarayanan, Jasper Snoek, Yarin Gal, Dustin Tran


  Access Paper or Ask Questions

Scalable and Flexible Deep Bayesian Optimization with Auxiliary Information for Scientific Problems


Apr 23, 2021
Samuel Kim, Peter Y. Lu, Charlotte Loh, Jamie Smith, Jasper Snoek, Marin Soljačić

* 18 pages, 12 figures 

  Access Paper or Ask Questions

Combining Ensembles and Data Augmentation can Harm your Calibration


Oct 19, 2020
Yeming Wen, Ghassen Jerfel, Rafael Muller, Michael W. Dusenberry, Jasper Snoek, Balaji Lakshminarayanan, Dustin Tran


  Access Paper or Ask Questions

Exploring the Uncertainty Properties of Neural Networks' Implicit Priors in the Infinite-Width Limit


Oct 14, 2020
Ben Adlam, Jaehoon Lee, Lechao Xiao, Jeffrey Pennington, Jasper Snoek

* 23 pages, 11 figures 

  Access Paper or Ask Questions

Training independent subnetworks for robust prediction


Oct 13, 2020
Marton Havasi, Rodolphe Jenatton, Stanislav Fort, Jeremiah Zhe Liu, Jasper Snoek, Balaji Lakshminarayanan, Andrew M. Dai, Dustin Tran


  Access Paper or Ask Questions

Empirical Frequentist Coverage of Deep Learning Uncertainty Quantification Procedures


Oct 06, 2020
Benjamin Kompa, Jasper Snoek, Andrew Beam

* 11 pages, 8 figures 

  Access Paper or Ask Questions

A Spectral Energy Distance for Parallel Speech Synthesis


Aug 03, 2020
Alexey A. Gritsenko, Tim Salimans, Rianne van den Berg, Jasper Snoek, Nal Kalchbrenner


  Access Paper or Ask Questions

Cold Posteriors and Aleatoric Uncertainty


Jul 31, 2020
Ben Adlam, Jasper Snoek, Samuel L. Smith

* ICML workshop on Uncertainty and Robustness in Deep Learning (2020) 
* 5 pages, 3 figures 

  Access Paper or Ask Questions

Evaluating Prediction-Time Batch Normalization for Robustness under Covariate Shift


Jul 17, 2020
Zachary Nado, Shreyas Padhy, D. Sculley, Alexander D'Amour, Balaji Lakshminarayanan, Jasper Snoek


  Access Paper or Ask Questions

Revisiting One-vs-All Classifiers for Predictive Uncertainty and Out-of-Distribution Detection in Neural Networks


Jul 10, 2020
Shreyas Padhy, Zachary Nado, Jie Ren, Jeremiah Liu, Jasper Snoek, Balaji Lakshminarayanan


  Access Paper or Ask Questions

Hyperparameter Ensembles for Robustness and Uncertainty Quantification


Jun 24, 2020
Florian Wenzel, Jasper Snoek, Dustin Tran, Rodolphe Jenatton


  Access Paper or Ask Questions

Efficient and Scalable Bayesian Neural Nets with Rank-1 Factors


May 14, 2020
Michael W. Dusenberry, Ghassen Jerfel, Yeming Wen, Yi-an Ma, Jasper Snoek, Katherine Heller, Balaji Lakshminarayanan, Dustin Tran

* Code available at https://github.com/google/edward2 

  Access Paper or Ask Questions

Weighting Is Worth the Wait: Bayesian Optimization with Importance Sampling


Feb 23, 2020
Setareh Ariafar, Zelda Mariet, Ehsan Elhamifar, Dana Brooks, Jennifer Dy, Jasper Snoek


  Access Paper or Ask Questions

The k-tied Normal Distribution: A Compact Parameterization of Gaussian Mean Field Posteriors in Bayesian Neural Networks


Feb 07, 2020
Jakub Swiatkowski, Kevin Roth, Bastiaan S. Veeling, Linh Tran, Joshua V. Dillon, Stephan Mandt, Jasper Snoek, Tim Salimans, Rodolphe Jenatton, Sebastian Nowozin


  Access Paper or Ask Questions

How Good is the Bayes Posterior in Deep Neural Networks Really?


Feb 06, 2020
Florian Wenzel, Kevin Roth, Bastiaan S. Veeling, Jakub Świątkowski, Linh Tran, Stephan Mandt, Jasper Snoek, Tim Salimans, Rodolphe Jenatton, Sebastian Nowozin


  Access Paper or Ask Questions

Hydra: Preserving Ensemble Diversity for Model Distillation


Jan 14, 2020
Linh Tran, Bastiaan S. Veeling, Kevin Roth, Jakub Swiatkowski, Joshua V. Dillon, Jasper Snoek, Stephan Mandt, Tim Salimans, Sebastian Nowozin, Rodolphe Jenatton


  Access Paper or Ask Questions

Likelihood Ratios for Out-of-Distribution Detection


Jun 07, 2019
Jie Ren, Peter J. Liu, Emily Fertig, Jasper Snoek, Ryan Poplin, Mark A. DePristo, Joshua V. Dillon, Balaji Lakshminarayanan


  Access Paper or Ask Questions

Can You Trust Your Model's Uncertainty? Evaluating Predictive Uncertainty Under Dataset Shift


Jun 06, 2019
Yaniv Ovadia, Emily Fertig, Jie Ren, Zachary Nado, D Sculley, Sebastian Nowozin, Joshua V. Dillon, Balaji Lakshminarayanan, Jasper Snoek


  Access Paper or Ask Questions

DPPNet: Approximating Determinantal Point Processes with Deep Networks


Jan 07, 2019
Zelda Mariet, Yaniv Ovadia, Jasper Snoek


  Access Paper or Ask Questions

Avoiding a Tragedy of the Commons in the Peer Review Process


Dec 18, 2018
D Sculley, Jasper Snoek, Alex Wiltschko

* Appeared in the 2018 Advances in Neural Information Processing Systems Workshop on Critiquing and Correcting Trends in Machine Learning 

  Access Paper or Ask Questions

Deep Bayesian Bandits Showdown: An Empirical Comparison of Bayesian Deep Networks for Thompson Sampling


Feb 26, 2018
Carlos Riquelme, George Tucker, Jasper Snoek

* Sixth International Conference on Learning Representations, ICLR 2018 

  Access Paper or Ask Questions

Learning Latent Permutations with Gumbel-Sinkhorn Networks


Feb 23, 2018
Gonzalo Mena, David Belanger, Scott Linderman, Jasper Snoek

* ICLR 2018 

  Access Paper or Ask Questions

Scalable Bayesian Optimization Using Deep Neural Networks


Jul 13, 2015
Jasper Snoek, Oren Rippel, Kevin Swersky, Ryan Kiros, Nadathur Satish, Narayanan Sundaram, Md. Mostofa Ali Patwary, Prabhat, Ryan P. Adams


  Access Paper or Ask Questions

Spectral Representations for Convolutional Neural Networks


Jun 11, 2015
Oren Rippel, Jasper Snoek, Ryan P. Adams


  Access Paper or Ask Questions

Raiders of the Lost Architecture: Kernels for Bayesian Optimization in Conditional Parameter Spaces


Sep 14, 2014
Kevin Swersky, David Duvenaud, Jasper Snoek, Frank Hutter, Michael A. Osborne

* 6 pages, 3 figures. Appeared in the NIPS 2013 workshop on Bayesian optimization 

  Access Paper or Ask Questions

Freeze-Thaw Bayesian Optimization


Jun 16, 2014
Kevin Swersky, Jasper Snoek, Ryan Prescott Adams


  Access Paper or Ask Questions

Input Warping for Bayesian Optimization of Non-stationary Functions


Jun 11, 2014
Jasper Snoek, Kevin Swersky, Richard S. Zemel, Ryan P. Adams


  Access Paper or Ask Questions