Jasper Snoek
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
20
Venues
6
Active years
2010–2025
Best venue rank
A*
Where they publish
Papers
20 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2025 | ICLR | Bayesian Optimization via Continual Variational Last Layer Training. | Paul Brunzema, Mikkel Jordahn, John Willes, Sebastian Trimpe, Jasper Snoek, James Harrison |
| 2024 | ICLR | Variational Bayesian Last Layers. | James Harrison, John Willes, Jasper Snoek |
| 2022 | AISTATS | Predicting the utility of search spaces for black-box optimization: a simple, budget-aware approach. | Setareh Ariafar, Justin Gilmer, Zachary Nado, Jasper Snoek, Rodolphe Jenatton, George E. Dahl |
| 2021 | AISTATS | Faster & More Reliable Tuning of Neural Networks: Bayesian Optimization with Importance Sampling. | Setareh Ariafar, Zelda Mariet, Dana H. Brooks, Jennifer G. Dy, Jasper Snoek |
| 2021 | ICLR | Exploring the Uncertainty Properties of Neural Networks' Implicit Priors in the Infinite-Width Limit. | Ben Adlam, Jaehoon Lee, Lechao Xiao, Jeffrey Pennington, Jasper Snoek |
| 2021 | ICLR | Training independent subnetworks for robust prediction. | Marton Havasi, Rodolphe Jenatton, Stanislav Fort, Jeremiah Zhe Liu, Jasper Snoek, Balaji Lakshminarayanan, Andrew Mingbo Dai, Dustin Tran |
| 2021 | ICLR | Combining Ensembles and Data Augmentation Can Harm Your Calibration. | Yeming Wen, Ghassen Jerfel, Rafael Muller, Michael W. Dusenberry, Jasper Snoek, Balaji Lakshminarayanan, Dustin Tran |
| 2020 | ICML | Efficient and Scalable Bayesian Neural Nets with Rank-1 Factors. | Michael Dusenberry, Ghassen Jerfel, Yeming Wen, Yi-An Ma, Jasper Snoek, Katherine A. Heller, Balaji Lakshminarayanan, Dustin Tran |
| 2020 | ICML | The k-tied Normal Distribution: A Compact Parameterization of Gaussian Mean Field Posteriors in Bayesian Neural Networks. | Jakub Swiatkowski, Kevin Roth, Bastiaan S. Veeling, Linh Tran, Joshua V. Dillon, Jasper Snoek, Stephan Mandt, Tim Salimans, Rodolphe Jenatton, Sebastian Nowozin |
| 2020 | ICML | How Good is the Bayes Posterior in Deep Neural Networks Really? | Florian Wenzel, Kevin Roth, Bastiaan S. Veeling, Jakub Swiatkowski, Linh Tran, Stephan Mandt, Jasper Snoek, Tim Salimans, Rodolphe Jenatton, Sebastian Nowozin |
| 2019 | ICLR | On the relationship between Normalising Flows and Variational- and Denoising Autoencoders. | Alexey A. Gritsenko, Jasper Snoek, Tim Salimans |
| 2018 | ICLR | Learning Latent Permutations with Gumbel-Sinkhorn Networks. | Gonzalo E. Mena, David Belanger, Scott W. Linderman, Jasper Snoek |
| 2018 | ICLR | Stochastic Gradient Langevin dynamics that Exploit Neural Network Structure. | Zachary Nado, Jasper Snoek, Roger B. Grosse, David Duvenaud, Bowen Xu, James Martens |
| 2018 | ICLR | Deep Bayesian Bandits Showdown: An Empirical Comparison of Bayesian Deep Networks for Thompson Sampling. | Carlos Riquelme, George Tucker, Jasper Snoek |
| 2018 | ICLR | Winner's Curse? On Pace, Progress, and Empirical Rigor. | D. Sculley, Jasper Snoek, Alexander B. Wiltschko, Ali Rahimi |
| 2015 | ICML | Scalable Bayesian Optimization Using Deep Neural Networks. | Jasper Snoek, Oren Rippel, Kevin Swersky, Ryan Kiros, Nadathur Satish, Narayanan Sundaram, Md. Mostofa Ali Patwary, Prabhat, Ryan P. Adams |
| 2014 | ICML | Input Warping for Bayesian Optimization of Non-Stationary Functions. | Jasper Snoek, Kevin Swersky, Richard S. Zemel, Ryan P. Adams |
| 2014 | UAI | Bayesian Optimization with Unknown Constraints. | Michael A. Gelbart, Jasper Snoek, Ryan P. Adams |
| 2011 | ICDM | From Videos to Places: Geolocating the World's Videos. | Jasper Snoek, Luciano Sbaiz, Hrishikesh B. Aradhye |
| 2010 | CVPR | Automatic segmentation of video to aid the study of faucet usability for older adults. | Jasper Snoek, Babak Taati, Yulia Eskin, Alex Mihailidis |