Jasper Snoek

Publication Activity (10 Years)

Years Active: 2006-2024
Publications (10 Years): 58

Top Topics

Variational Bayesian

Top Venues

Publications

James Harrison, John Willes, Jasper Snoek
Variational Bayesian Last Layers. ICLR (2024)
James Harrison, John Willes, Jasper Snoek
Variational Bayesian Last Layers. CoRR (2024)
Avi Singh, John D. Co-Reyes, Rishabh Agarwal, Ankesh Anand, Piyush Patil, Xavier Garcia, Peter J. Liu, James Harrison, Jaehoon Lee, Kelvin Xu, Aaron T. Parisi, Abhishek Kumar, Alexander A. Alemi, Alex Rizkowsky, Azade Nova, Ben Adlam, Bernd Bohnet, Gamaleldin Fathy Elsayed, Hanie Sedghi, Igor Mordatch, Isabelle Simpson, Izzeddin Gur, Jasper Snoek, Jeffrey Pennington, Jiri Hron, Kathleen Kenealy, Kevin Swersky, Kshiteej Mahajan, Laura Culp, Lechao Xiao, Maxwell L. Bileschi, Noah Constant, Roman Novak, Rosanne Liu, Tris Warkentin, Yundi Qian, Yamini Bansal, Ethan Dyer, Behnam Neyshabur, Jascha Sohl-Dickstein, Noah Fiedel
Beyond Human Data: Scaling Self-Training for Problem-Solving with Language Models. Trans. Mach. Learn. Res. 2024 (2024)
Avi Singh, John D. Co-Reyes, Rishabh Agarwal, Ankesh Anand, Piyush Patil, Xavier Garcia, Peter J. Liu, James Harrison, Jaehoon Lee, Kelvin Xu, Aaron Parisi, Abhishek Kumar, Alex Alemi, Alex Rizkowsky, Azade Nova, Ben Adlam, Bernd Bohnet, Gamaleldin F. Elsayed, Hanie Sedghi, Igor Mordatch, Isabelle Simpson, Izzeddin Gur, Jasper Snoek, Jeffrey Pennington, Jiri Hron, Kathleen Kenealy, Kevin Swersky, Kshiteej Mahajan, Laura Culp, Lechao Xiao, Maxwell L. Bileschi, Noah Constant, Roman Novak, Rosanne Liu, Tris Warkentin, Yundi Qian, Yamini Bansal, Ethan Dyer, Behnam Neyshabur, Jascha Sohl-Dickstein, Noah Fiedel
Beyond Human Data: Scaling Self-Training for Problem-Solving with Language Models. CoRR (2023)
Jeremiah Zhe Liu, Shreyas Padhy, Jie Ren, Zi Lin, Yeming Wen, Ghassen Jerfel, Zachary Nado, Jasper Snoek, Dustin Tran, Balaji Lakshminarayanan
A Simple Approach to Improve Single-Model Deep Uncertainty via Distance-Awareness. J. Mach. Learn. Res. 24 (2023)
Ben Adlam, Jaehoon Lee, Shreyas Padhy, Zachary Nado, Jasper Snoek
Kernel Regression with Infinite-Width Neural Networks on Millions of Examples. CoRR (2023)
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
Sparse MoEs meet Efficient Ensembles. Trans. Mach. Learn. Res. 2022 (2022)
Jeremiah Zhe Liu, Shreyas Padhy, Jie Ren, Zi Lin, Yeming Wen, Ghassen Jerfel, Zack Nado, Jasper Snoek, Dustin Tran, Balaji Lakshminarayanan
A Simple Approach to Improve Single-Model Deep Uncertainty via Distance-Awareness. CoRR (2022)
Dustin Tran, Jeremiah Liu, Michael W. Dusenberry, Du Phan, Mark Collier, Jie Ren, Kehang Han, Zi Wang, Zelda Mariet, Huiyi Hu, Neil Band, Tim G. J. Rudner, Karan Singhal, Zachary Nado, Joost van Amersfoort, Andreas Kirsch, Rodolphe Jenatton, Nithum Thain, Honglin Yuan, Kelly Buchanan, Kevin Murphy, D. Sculley, Yarin Gal, Zoubin Ghahramani, Jasper Snoek, Balaji Lakshminarayanan
Plex: Towards Reliability using Pretrained Large Model Extensions. CoRR (2022)
Setareh Ariafar, Justin Gilmer, Zachary Nado, Jasper Snoek, Rodolphe Jenatton, George E. Dahl
Predicting the utility of search spaces for black-box optimization: a simple, budget-aware approach. AISTATS (2022)
Samuel Kim, Peter Y. Lu, Charlotte Loh, Jamie Smith, Jasper Snoek, Marin Soljacic
Deep Learning for Bayesian Optimization of Scientific Problems with High-Dimensional Structure. Trans. Mach. Learn. Res. 2022 (2022)
Zi Wang, George E. Dahl, Kevin Swersky, Chansoo Lee, Zelda Mariet, Zachary Nado, Justin Gilmer, Jasper Snoek, Zoubin Ghahramani
Pre-training helps Bayesian optimization too. CoRR (2022)
Benjamin Kompa, Jasper Snoek, Andrew L. Beam
Empirical Frequentist Coverage of Deep Learning Uncertainty Quantification Procedures. Entropy 23 (12) (2021)
Setareh Ariafar, Zelda Mariet, Dana H. Brooks, Jennifer G. Dy, Jasper Snoek
Faster & More Reliable Tuning of Neural Networks: Bayesian Optimization with Importance Sampling. AISTATS (2021)
Zi Wang, George E. Dahl, Kevin Swersky, Chansoo Lee, Zelda Mariet, Zachary Nado, Justin Gilmer, Jasper Snoek, Zoubin Ghahramani
Automatic prior selection for meta Bayesian optimization with a case study on tuning deep neural network optimizers. CoRR (2021)
Marton Havasi, Jasper Snoek, Dustin Tran, Jonathan Gordon, José Miguel Hernández-Lobato
Sampling the Variational Posterior with Local Refinement. Entropy 23 (11) (2021)
Ben Adlam, Jaehoon Lee, Lechao Xiao, Jeffrey Pennington, Jasper Snoek
Exploring the Uncertainty Properties of Neural Networks' Implicit Priors in the Infinite-Width Limit. ICLR (2021)
Setareh Ariafar, Justin Gilmer, Zachary Nado, Jasper Snoek, Rodolphe Jenatton, George E. Dahl
Predicting the utility of search spaces for black-box optimization: a simple, budget-aware approach. CoRR (2021)
Yeming Wen, Ghassen Jerfel, Rafael Muller, Michael W. Dusenberry, Jasper Snoek, Balaji Lakshminarayanan, Dustin Tran
Combining Ensembles and Data Augmentation Can Harm Your Calibration. ICLR (2021)
Samuel Kim, Peter Y. Lu, Charlotte Loh, Jamie Smith, Jasper Snoek, Marin Soljacic
Scalable and Flexible Deep Bayesian Optimization with Auxiliary Information for Scientific Problems. CoRR (2021)
Marton Havasi, Rodolphe Jenatton, Stanislav Fort, Jeremiah Zhe Liu, Jasper Snoek, Balaji Lakshminarayanan, Andrew Mingbo Dai, Dustin Tran
Training independent subnetworks for robust prediction. ICLR (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
Uncertainty Baselines: Benchmarks for Uncertainty & Robustness in Deep Learning. CoRR (2021)
Benjamin Kompa, Jasper Snoek, Andrew L. Beam
Second opinion needed: communicating uncertainty in medical machine learning. npj Digit. Medicine 4 (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
Sparse MoEs meet Efficient Ensembles. CoRR (2021)
Yeming Wen, Ghassen Jerfel, Rafael Muller, Michael W. Dusenberry, Jasper Snoek, Balaji Lakshminarayanan, Dustin Tran
Combining Ensembles and Data Augmentation can Harm your Calibration. CoRR (2020)
Alexey A. Gritsenko, Tim Salimans, Rianne van den Berg, Jasper Snoek, Nal Kalchbrenner
A Spectral Energy Distance for Parallel Speech Synthesis. NeurIPS (2020)
Setareh Ariafar, Zelda Mariet, Ehsan Elhamifar, Dana H. Brooks, Jennifer G. Dy, Jasper Snoek
Weighting Is Worth the Wait: Bayesian Optimization with Importance Sampling. CoRR (2020)
Ben Adlam, Jasper Snoek, Samuel L. Smith
Cold Posteriors and Aleatoric Uncertainty. CoRR (2020)
Michael W. Dusenberry, Ghassen Jerfel, Yeming Wen, Yi-An Ma, Jasper Snoek, Katherine A. Heller, Balaji Lakshminarayanan, Dustin Tran
Efficient and Scalable Bayesian Neural Nets with Rank-1 Factors. CoRR (2020)
Shreyas Padhy, Zachary Nado, Jie Ren, Jeremiah Z. Liu, Jasper Snoek, Balaji Lakshminarayanan
Revisiting One-vs-All Classifiers for Predictive Uncertainty and Out-of-Distribution Detection in Neural Networks. CoRR (2020)
Zachary Nado, Shreyas Padhy, D. Sculley, Alexander D'Amour, Balaji Lakshminarayanan, Jasper Snoek
Evaluating Prediction-Time Batch Normalization for Robustness under Covariate Shift. CoRR (2020)
Alexey A. Gritsenko, Tim Salimans, Rianne van den Berg, Jasper Snoek, Nal Kalchbrenner
A Spectral Energy Distance for Parallel Speech Synthesis. CoRR (2020)
Florian Wenzel, Jasper Snoek, Dustin Tran, Rodolphe Jenatton
Hyperparameter Ensembles for Robustness and Uncertainty Quantification. NeurIPS (2020)
Florian Wenzel, Jasper Snoek, Dustin Tran, Rodolphe Jenatton
Hyperparameter Ensembles for Robustness and Uncertainty Quantification. CoRR (2020)
Michael Dusenberry, Ghassen Jerfel, Yeming Wen, Yi-An Ma, Jasper Snoek, Katherine A. Heller, Balaji Lakshminarayanan, Dustin Tran
Efficient and Scalable Bayesian Neural Nets with Rank-1 Factors. ICML (2020)
Linh Tran, Bastiaan S. Veeling, Kevin Roth, Jakub Swiatkowski, Joshua V. Dillon, Jasper Snoek, Stephan Mandt, Tim Salimans, Sebastian Nowozin, Rodolphe Jenatton
Hydra: Preserving Ensemble Diversity for Model Distillation. CoRR (2020)
Marton Havasi, Rodolphe Jenatton, Stanislav Fort, Jeremiah Zhe Liu, Jasper Snoek, Balaji Lakshminarayanan, Andrew M. Dai, Dustin Tran
Training independent subnetworks for robust prediction. CoRR (2020)
Jakub Swiatkowski, Kevin Roth, Bastiaan S. Veeling, Linh Tran, Joshua V. Dillon, Stephan Mandt, Jasper Snoek, Tim Salimans, Rodolphe Jenatton, Sebastian Nowozin
The k-tied Normal Distribution: A Compact Parameterization of Gaussian Mean Field Posteriors in Bayesian Neural Networks. CoRR (2020)
Jakub Swiatkowski, Kevin Roth, Bastiaan S. Veeling, Linh Tran, Joshua V. Dillon, Jasper Snoek, Stephan Mandt, Tim Salimans, Rodolphe Jenatton, Sebastian Nowozin
The k-tied Normal Distribution: A Compact Parameterization of Gaussian Mean Field Posteriors in Bayesian Neural Networks. ICML (2020)
Ben Adlam, Jaehoon Lee, Lechao Xiao, Jeffrey Pennington, Jasper Snoek
Exploring the Uncertainty Properties of Neural Networks' Implicit Priors in the Infinite-Width Limit. CoRR (2020)
Florian Wenzel, Kevin Roth, Bastiaan S. Veeling, Jakub Swiatkowski, Linh Tran, Stephan Mandt, Jasper Snoek, Tim Salimans, Rodolphe Jenatton, Sebastian Nowozin
How Good is the Bayes Posterior in Deep Neural Networks Really? ICML (2020)
Benjamin Kompa, Jasper Snoek, Andrew Beam
Empirical Frequentist Coverage of Deep Learning Uncertainty Quantification Procedures. CoRR (2020)
Florian Wenzel, Kevin Roth, Bastiaan S. Veeling, Jakub Swiatkowski, Linh Tran, Stephan Mandt, Jasper Snoek, Tim Salimans, Rodolphe Jenatton, Sebastian Nowozin
How Good is the Bayes Posterior in Deep Neural Networks Really? CoRR (2020)
Jasper Snoek, Yaniv Ovadia, Emily Fertig, Balaji Lakshminarayanan, Sebastian Nowozin, D. Sculley, Joshua V. Dillon, Jie Ren, Zachary Nado
Can you trust your model's uncertainty? Evaluating predictive uncertainty under dataset shift. NeurIPS (2019)
D. Sculley, Jasper Snoek, Alexander B. Wiltschko
Avoiding a Tragedy of the Commons in the Peer Review Process. CoRR (2019)
Zelda Mariet, Yaniv Ovadia, Jasper Snoek
DPPNet: Approximating Determinantal Point Processes with Deep Networks. CoRR (2019)
Jie Ren, Peter J. Liu, Emily Fertig, Jasper Snoek, Ryan Poplin, Mark A. DePristo, Joshua V. Dillon, Balaji Lakshminarayanan
Likelihood Ratios for Out-of-Distribution Detection. CoRR (2019)
Yaniv Ovadia, Emily Fertig, Jie Ren, Zachary Nado, David Sculley, Sebastian Nowozin, Joshua V. Dillon, Balaji Lakshminarayanan, Jasper Snoek
Can You Trust Your Model's Uncertainty? Evaluating Predictive Uncertainty Under Dataset Shift. CoRR (2019)
Alexey A. Gritsenko, Jasper Snoek, Tim Salimans
On the relationship between Normalising Flows and Variational- and Denoising Autoencoders. DGS@ICLR (2019)
Zelda E. Mariet, Yaniv Ovadia, Jasper Snoek
DppNet: Approximating Determinantal Point Processes with Deep Networks. NeurIPS (2019)
Jie Ren, Peter J. Liu, Emily Fertig, Jasper Snoek, Ryan Poplin, Mark A. DePristo, Joshua V. Dillon, Balaji Lakshminarayanan
Likelihood Ratios for Out-of-Distribution Detection. NeurIPS (2019)
Carlos Riquelme, George Tucker, Jasper Snoek
Deep Bayesian Bandits Showdown: An Empirical Comparison of Bayesian Deep Networks for Thompson Sampling. CoRR (2018)
Gonzalo E. Mena, David Belanger, Scott W. Linderman, Jasper Snoek
Learning Latent Permutations with Gumbel-Sinkhorn Networks. CoRR (2018)
Zachary Nado, Jasper Snoek, Roger B. Grosse, David Duvenaud, Bowen Xu, James Martens
Stochastic Gradient Langevin dynamics that Exploit Neural Network Structure. ICLR (Workshop) (2018)
Carlos Riquelme, George Tucker, Jasper Snoek
Deep Bayesian Bandits Showdown: An Empirical Comparison of Bayesian Deep Networks for Thompson Sampling. ICLR (Poster) (2018)
D. Sculley, Jasper Snoek, Alexander B. Wiltschko, Ali Rahimi
Winner's Curse? On Pace, Progress, and Empirical Rigor. ICLR (Workshop) (2018)
Gonzalo E. Mena, David Belanger, Scott W. Linderman, Jasper Snoek
Learning Latent Permutations with Gumbel-Sinkhorn Networks. ICLR (Poster) (2018)
Ahmad Akl, Jasper Snoek, Alex Mihailidis
Unobtrusive Detection of Mild Cognitive Impairment in Older Adults Through Home Monitoring. IEEE J. Biomed. Health Informatics 21 (2) (2017)
Jasper Snoek, Oren Rippel, Kevin Swersky, Ryan Kiros, Nadathur Satish, Narayanan Sundaram, Md. Mostofa Ali Patwary, Prabhat, Ryan P. Adams
Scalable Bayesian Optimization Using Deep Neural Networks. ICML (2015)
Oren Rippel, Jasper Snoek, Ryan P. Adams
Spectral Representations for Convolutional Neural Networks. NIPS (2015)
Li-Wei H. Lehman, Mohammad M. Ghassemi, Jasper Snoek, Shamim Nemati
Patient Prognosis from Vital Sign Time Series: Combining Convolutional Neural Networks with a Dynamical Systems Approach. CinC (2015)
Oren Rippel, Jasper Snoek, Ryan P. Adams
Spectral Representations for Convolutional Neural Networks. CoRR (2015)
Jasper Snoek, Kevin Swersky, Richard S. Zemel, Ryan P. Adams
Input Warping for Bayesian Optimization of Non-stationary Functions. CoRR (2014)
Ahmad Akl, Jasper Snoek, Alex Mihailidis
Generalized Linear Models of home activity for automatic detection of mild cognitive impairment in older adults. EMBC (2014)
Jasper Snoek, Kevin Swersky, Richard S. Zemel, Ryan P. Adams
Input Warping for Bayesian Optimization of Non-Stationary Functions. ICML (2014)
Michael A. Gelbart, Jasper Snoek, Ryan P. Adams
Bayesian Optimization with Unknown Constraints. UAI (2014)
Kevin Swersky, Jasper Snoek, Ryan Prescott Adams
Freeze-Thaw Bayesian Optimization. CoRR (2014)
Mohammad M. Ghassemi, Li-Wei H. Lehman, Jasper Snoek, Shamim Nemati
Global Optimization Approaches for Parameter Tuning in Biomedical Signal Processing: A Focus of Multi-scale Entropy. CinC (2014)
Babak Taati, Jasper Snoek, Dionne M. Aleman, Ardeshir Ghavamzadeh
Data Mining in Bone Marrow Transplant Records to Identify Patients With High Odds of Survival. IEEE J. Biomed. Health Informatics 18 (1) (2014)
Michael A. Gelbart, Jasper Snoek, Ryan P. Adams
Bayesian Optimization with Unknown Constraints. CoRR (2014)
Babak Taati, Jasper Snoek, Alex Mihailidis
Video analysis for identifying human operation difficulties and faucet usability assessment. Neurocomputing 100 (2013)
Jasper Snoek, Richard S. Zemel, Ryan Prescott Adams
A Determinantal Point Process Latent Variable Model for Inhibition in Neural Spiking Data. NIPS (2013)
Kevin Swersky, Jasper Snoek, Ryan Prescott Adams
Multi-Task Bayesian Optimization. NIPS (2013)
Jasper Snoek, Ryan Prescott Adams, Hugo Larochelle
On Nonparametric Guidance for Learning Autoencoder Representations. AISTATS (2012)
Jasper Snoek, Babak Taati, Alex Mihailidis
An Automated Machine Learning Approach Applied to Robotic Stroke Rehabilitation. AAAI Fall Symposium: Artificial Intelligence for Gerontechnology (2012)
Jasper Snoek, Hugo Larochelle, Ryan P. Adams
Practical Bayesian Optimization of Machine Learning Algorithms. NIPS (2012)
Jasper Snoek, Hugo Larochelle, Ryan Prescott Adams
Practical Bayesian Optimization of Machine Learning Algorithms CoRR (2012)
Jasper Snoek, Ryan P. Adams, Hugo Larochelle
Nonparametric guidance of autoencoder representations using label information. J. Mach. Learn. Res. 13 (2012)
Michael Belshaw, Babak Taati, Jasper Snoek, Alex Mihailidis
Towards a single sensor passive solution for automated fall detection. EMBC (2011)
Jasper Snoek, Luciano Sbaiz, Hrishikesh B. Aradhye
From Videos to Places: Geolocating the World's Videos. ICDM Workshops (2011)
Babak Taati, Jasper Snoek, Alex Mihailidis
Towards Aging-in-Place: Automatic Assessment of Product Usability for Older Adults with Dementia. HISB (2011)
Jasper Snoek, Babak Taati, Yulia Eskin, Alex Mihailidis
Automatic segmentation of video to aid the study of faucet usability for older adults. CVPR Workshops (2010)
Babak Taati, Jasper Snoek, David Giesbrecht, Alex Mihailidis
Water Flow Detection in a Handwashing Task. CRV (2010)
Jasper Snoek, Jesse Hoey, Liam Stewart, Richard S. Zemel, Alex Mihailidis
Automated detection of unusual events on stairs. Image Vis. Comput. 27 (1-2) (2009)
Jasper Snoek, Jesse Hoey, Liam Stewart, Richard S. Zemel
Automated Detection of Unusual Events on Stairs. CRV (2006)