Jasper Snoek - RankMe

91 papers A* 15A 4Journal 52Unranked 19

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Expected Reward Prediction, with Applications to Model Routing. CoRR Kenan Hasanaliyev, Silas Alberti, Jenny Hamer, Dheeraj Rajagopal, Kevin Robinson, Jasper Snoek, Victor Veitch, Alexander Nicholas D'Amour
2025	A*	`conf`	Bayesian Optimization via Continual Variational Last Layer Training. ICLR Paul Brunzema, Mikkel Jordahn, John Willes, Sebastian Trimpe, Jasper Snoek, James Harrison
2024	J	`jnl`	Bayesian Optimization via Continual Variational Last Layer Training. CoRR Paul Brunzema, Mikkel Jordahn, John Willes, Sebastian Trimpe, Jasper Snoek, James Harrison
2024	J	`jnl`	Beyond Human Data: Scaling Self-Training for Problem-Solving with Language Models. Trans. Mach. Learn. Res. 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
2024	J	`jnl`	Pre-trained Gaussian Processes for Bayesian Optimization. J. Mach. Learn. Res. Zi Wang, George E. Dahl, Kevin Swersky, Chansoo Lee, Zachary Nado, Justin Gilmer, Jasper Snoek, Zoubin Ghahramani
2024	J	`jnl`	Training Language Models on the Knowledge Graph: Insights on Hallucinations and Their Detectability. CoRR Jiri Hron, Laura Culp, Gamaleldin F. Elsayed, Rosanne Liu, Ben Adlam, Maxwell L. Bileschi, Bernd Bohnet, JD Co-Reyes, Noah Fiedel, C. Daniel Freeman, Izzeddin Gur, Kathleen Kenealy, Jaehoon Lee, Peter J. Liu, Gaurav Mishra, Igor Mordatch, Azade Nova, Roman Novak, Aaron Parisi, Jeffrey Pennington, Alex Rizkowsky, Isabelle Simpson, Hanie Sedghi, Jascha Sohl-Dickstein, Kevin Swersky, Sharad Vikram, Tris Warkentin, Lechao Xiao, Kelvin Xu, Jasper Snoek, Simon Kornblith
2024	A*	`conf`	Variational Bayesian Last Layers. ICLR James Harrison, John Willes, Jasper Snoek
2024	J	`jnl`	Variational Bayesian Last Layers. CoRR James Harrison, John Willes, Jasper Snoek
2023	J	`jnl`	A Simple Approach to Improve Single-Model Deep Uncertainty via Distance-Awareness. J. Mach. Learn. Res. Jeremiah Zhe Liu, Shreyas Padhy, Jie Ren, Zi Lin, Yeming Wen, Ghassen Jerfel, Zachary Nado, Jasper Snoek, Dustin Tran, Balaji Lakshminarayanan
2023	J	`jnl`	Beyond Human Data: Scaling Self-Training for Problem-Solving with Language Models. CoRR 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
2023	J	`jnl`	Kernel Regression with Infinite-Width Neural Networks on Millions of Examples. CoRR Ben Adlam, Jaehoon Lee, Shreyas Padhy, Zachary Nado, Jasper Snoek
2022	J	`jnl`	A Simple Approach to Improve Single-Model Deep Uncertainty via Distance-Awareness. CoRR Jeremiah Zhe Liu, Shreyas Padhy, Jie Ren, Zi Lin, Yeming Wen, Ghassen Jerfel, Zack Nado, Jasper Snoek, Dustin Tran, Balaji Lakshminarayanan
2022	J	`jnl`	Deep Learning for Bayesian Optimization of Scientific Problems with High-Dimensional Structure. Trans. Mach. Learn. Res. Samuel Kim, Peter Y. Lu, Charlotte Loh, Jamie Smith, Jasper Snoek, Marin Soljacic
2022	J	`jnl`	Plex: Towards Reliability using Pretrained Large Model Extensions. CoRR Dustin Tran, Jeremiah Z. 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
2022	J	`jnl`	Pre-training helps Bayesian optimization too. CoRR Zi Wang, George E. Dahl, Kevin Swersky, Chansoo Lee, Zelda Mariet, Zachary Nado, Justin Gilmer, Jasper Snoek, Zoubin Ghahramani
2022	A	`conf`	Predicting the utility of search spaces for black-box optimization: a simple, budget-aware approach. AISTATS Setareh Ariafar, Justin Gilmer, Zachary Nado, Jasper Snoek, Rodolphe Jenatton, George E. Dahl
2022	J	`jnl`	Sparse MoEs meet Efficient Ensembles. Trans. Mach. Learn. Res. 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
2021	J	`jnl`	Automatic prior selection for meta Bayesian optimization with a case study on tuning deep neural network optimizers. CoRR Zi Wang, George E. Dahl, Kevin Swersky, Chansoo Lee, Zelda Mariet, Zachary Nado, Justin Gilmer, Jasper Snoek, Zoubin Ghahramani
2021	A*	`conf`	Combining Ensembles and Data Augmentation Can Harm Your Calibration. ICLR Yeming Wen, Ghassen Jerfel, Rafael Muller, Michael W. Dusenberry, Jasper Snoek, Balaji Lakshminarayanan, Dustin Tran
2021	J	`jnl`	Empirical Frequentist Coverage of Deep Learning Uncertainty Quantification Procedures. Entropy Benjamin Kompa, Jasper Snoek, Andrew L. Beam
2021	A*	`conf`	Exploring the Uncertainty Properties of Neural Networks' Implicit Priors in the Infinite-Width Limit. ICLR Ben Adlam, Jaehoon Lee, Lechao Xiao, Jeffrey Pennington, Jasper Snoek
2021	A	`conf`	Faster & More Reliable Tuning of Neural Networks: Bayesian Optimization with Importance Sampling. AISTATS Setareh Ariafar, Zelda Mariet, Dana H. Brooks, Jennifer G. Dy, Jasper Snoek
2021	J	`jnl`	Predicting the utility of search spaces for black-box optimization: a simple, budget-aware approach. CoRR Setareh Ariafar, Justin Gilmer, Zachary Nado, Jasper Snoek, Rodolphe Jenatton, George E. Dahl
2021	J	`jnl`	Sampling the Variational Posterior with Local Refinement. Entropy Marton Havasi, Jasper Snoek, Dustin Tran, Jonathan Gordon, José Miguel Hernández-Lobato
2021	J	`jnl`	Scalable and Flexible Deep Bayesian Optimization with Auxiliary Information for Scientific Problems. CoRR Samuel Kim, Peter Y. Lu, Charlotte Loh, Jamie Smith, Jasper Snoek, Marin Soljacic
2021	J	`jnl`	Second opinion needed: communicating uncertainty in medical machine learning. npj Digit. Medicine Benjamin Kompa, Jasper Snoek, Andrew L. Beam
2021	J	`jnl`	Sparse MoEs meet Efficient Ensembles. CoRR 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
2021	A*	`conf`	Training independent subnetworks for robust prediction. ICLR Marton Havasi, Rodolphe Jenatton, Stanislav Fort, Jeremiah Zhe Liu, Jasper Snoek, Balaji Lakshminarayanan, Andrew Mingbo Dai, Dustin Tran
2021	J	`jnl`	Uncertainty Baselines: Benchmarks for Uncertainty & Robustness in Deep Learning. CoRR Zachary Nado, Neil Band, Mark Collier, Josip Djolonga, Michael W. Dusenberry, Sebastian Farquhar, Angelos Filos, Marton Havasi, Rodolphe Jenatton, Ghassen Jerfel, Jeremiah Z. 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
2020	A*	`conf`	A Spectral Energy Distance for Parallel Speech Synthesis. NeurIPS Alexey A. Gritsenko, Tim Salimans, Rianne van den Berg, Jasper Snoek, Nal Kalchbrenner
2020	J	`jnl`	A Spectral Energy Distance for Parallel Speech Synthesis. CoRR Alexey A. Gritsenko, Tim Salimans, Rianne van den Berg, Jasper Snoek, Nal Kalchbrenner
2020	J	`jnl`	Cold Posteriors and Aleatoric Uncertainty. CoRR Ben Adlam, Jasper Snoek, Samuel L. Smith
2020	J	`jnl`	Combining Ensembles and Data Augmentation can Harm your Calibration. CoRR Yeming Wen, Ghassen Jerfel, Rafael Muller, Michael W. Dusenberry, Jasper Snoek, Balaji Lakshminarayanan, Dustin Tran
2020	A*	`conf`	Efficient and Scalable Bayesian Neural Nets with Rank-1 Factors. ICML Michael Dusenberry, Ghassen Jerfel, Yeming Wen, Yi-An Ma, Jasper Snoek, Katherine A. Heller, Balaji Lakshminarayanan, Dustin Tran
2020	J	`jnl`	Efficient and Scalable Bayesian Neural Nets with Rank-1 Factors. CoRR Michael W. Dusenberry, Ghassen Jerfel, Yeming Wen, Yi-An Ma, Jasper Snoek, Katherine A. Heller, Balaji Lakshminarayanan, Dustin Tran
2020	J	`jnl`	Empirical Frequentist Coverage of Deep Learning Uncertainty Quantification Procedures. CoRR Benjamin Kompa, Jasper Snoek, Andrew Beam
2020	J	`jnl`	Evaluating Prediction-Time Batch Normalization for Robustness under Covariate Shift. CoRR Zachary Nado, Shreyas Padhy, D. Sculley, Alexander D'Amour, Balaji Lakshminarayanan, Jasper Snoek
2020	J	`jnl`	Exploring the Uncertainty Properties of Neural Networks' Implicit Priors in the Infinite-Width Limit. CoRR Ben Adlam, Jaehoon Lee, Lechao Xiao, Jeffrey Pennington, Jasper Snoek
2020	A*	`conf`	How Good is the Bayes Posterior in Deep Neural Networks Really? ICML Florian Wenzel, Kevin Roth, Bastiaan S. Veeling, Jakub Swiatkowski, Linh Tran, Stephan Mandt, Jasper Snoek, Tim Salimans, Rodolphe Jenatton, Sebastian Nowozin
2020	J	`jnl`	How Good is the Bayes Posterior in Deep Neural Networks Really? CoRR Florian Wenzel, Kevin Roth, Bastiaan S. Veeling, Jakub Swiatkowski, Linh Tran, Stephan Mandt, Jasper Snoek, Tim Salimans, Rodolphe Jenatton, Sebastian Nowozin
2020	J	`jnl`	Hydra: Preserving Ensemble Diversity for Model Distillation. CoRR Linh Tran, Bastiaan S. Veeling, Kevin Roth, Jakub Swiatkowski, Joshua V. Dillon, Jasper Snoek, Stephan Mandt, Tim Salimans, Sebastian Nowozin, Rodolphe Jenatton
2020	A*	`conf`	Hyperparameter Ensembles for Robustness and Uncertainty Quantification. NeurIPS Florian Wenzel, Jasper Snoek, Dustin Tran, Rodolphe Jenatton
2020	J	`jnl`	Hyperparameter Ensembles for Robustness and Uncertainty Quantification. CoRR Florian Wenzel, Jasper Snoek, Dustin Tran, Rodolphe Jenatton
2020	J	`jnl`	Revisiting One-vs-All Classifiers for Predictive Uncertainty and Out-of-Distribution Detection in Neural Networks. CoRR Shreyas Padhy, Zachary Nado, Jie Ren, Jeremiah Z. Liu, Jasper Snoek, Balaji Lakshminarayanan
2020	A*	`conf`	The k-tied Normal Distribution: A Compact Parameterization of Gaussian Mean Field Posteriors in Bayesian Neural Networks. ICML Jakub Swiatkowski, Kevin Roth, Bastiaan S. Veeling, Linh Tran, Joshua V. Dillon, Jasper Snoek, Stephan Mandt, Tim Salimans, Rodolphe Jenatton, Sebastian Nowozin
2020	J	`jnl`	The k-tied Normal Distribution: A Compact Parameterization of Gaussian Mean Field Posteriors in Bayesian Neural Networks. CoRR Jakub Swiatkowski, Kevin Roth, Bastiaan S. Veeling, Linh Tran, Joshua V. Dillon, Stephan Mandt, Jasper Snoek, Tim Salimans, Rodolphe Jenatton, Sebastian Nowozin
2020	J	`jnl`	Training independent subnetworks for robust prediction. CoRR Marton Havasi, Rodolphe Jenatton, Stanislav Fort, Jeremiah Zhe Liu, Jasper Snoek, Balaji Lakshminarayanan, Andrew M. Dai, Dustin Tran
2020	J	`jnl`	Weighting Is Worth the Wait: Bayesian Optimization with Importance Sampling. CoRR Setareh Ariafar, Zelda Mariet, Ehsan Elhamifar, Dana H. Brooks, Jennifer G. Dy, Jasper Snoek
2019	J	`jnl`	Avoiding a Tragedy of the Commons in the Peer Review Process. CoRR D. Sculley, Jasper Snoek, Alexander B. Wiltschko
2019	J	`jnl`	Can You Trust Your Model's Uncertainty? Evaluating Predictive Uncertainty Under Dataset Shift. CoRR Yaniv Ovadia, Emily Fertig, Jie Ren, Zachary Nado, David Sculley, Sebastian Nowozin, Joshua V. Dillon, Balaji Lakshminarayanan, Jasper Snoek
2019	A*	`conf`	Can you trust your model's uncertainty? Evaluating predictive uncertainty under dataset shift. NeurIPS Jasper Snoek, Yaniv Ovadia, Emily Fertig, Balaji Lakshminarayanan, Sebastian Nowozin, D. Sculley, Joshua V. Dillon, Jie Ren, Zachary Nado
2019	J	`jnl`	DPPNet: Approximating Determinantal Point Processes with Deep Networks. CoRR Zelda Mariet, Yaniv Ovadia, Jasper Snoek
2019	A*	`conf`	DppNet: Approximating Determinantal Point Processes with Deep Networks. NeurIPS Zelda E. Mariet, Yaniv Ovadia, Jasper Snoek
2019	A*	`conf`	Likelihood Ratios for Out-of-Distribution Detection. NeurIPS Jie Ren, Peter J. Liu, Emily Fertig, Jasper Snoek, Ryan Poplin, Mark A. DePristo, Joshua V. Dillon, Balaji Lakshminarayanan
2019	J	`jnl`	Likelihood Ratios for Out-of-Distribution Detection. CoRR Jie Ren, Peter J. Liu, Emily Fertig, Jasper Snoek, Ryan Poplin, Mark A. DePristo, Joshua V. Dillon, Balaji Lakshminarayanan
2019	—	`conf`	On the relationship between Normalising Flows and Variational- and Denoising Autoencoders. DGS@ICLR Alexey A. Gritsenko, Jasper Snoek, Tim Salimans
2018	—	`conf`	Deep Bayesian Bandits Showdown: An Empirical Comparison of Bayesian Deep Networks for Thompson Sampling. ICLR (Poster) Carlos Riquelme, George Tucker, Jasper Snoek
2018	J	`jnl`	Deep Bayesian Bandits Showdown: An Empirical Comparison of Bayesian Deep Networks for Thompson Sampling. CoRR Carlos Riquelme, George Tucker, Jasper Snoek
2018	—	`conf`	Learning Latent Permutations with Gumbel-Sinkhorn Networks. ICLR (Poster) Gonzalo E. Mena, David Belanger, Scott W. Linderman, Jasper Snoek
2018	J	`jnl`	Learning Latent Permutations with Gumbel-Sinkhorn Networks. CoRR Gonzalo E. Mena, David Belanger, Scott W. Linderman, Jasper Snoek
2018	—	`conf`	Stochastic Gradient Langevin dynamics that Exploit Neural Network Structure. ICLR (Workshop) Zachary Nado, Jasper Snoek, Roger B. Grosse, David Duvenaud, Bowen Xu, James Martens
2018	—	`conf`	Winner's Curse? On Pace, Progress, and Empirical Rigor. ICLR (Workshop) D. Sculley, Jasper Snoek, Alexander B. Wiltschko, Ali Rahimi
2017	J	`jnl`	Unobtrusive Detection of Mild Cognitive Impairment in Older Adults Through Home Monitoring. IEEE J. Biomed. Health Informatics Ahmad Akl, Jasper Snoek, Alex Mihailidis
2015	—	`conf`	Patient Prognosis from Vital Sign Time Series: Combining Convolutional Neural Networks with a Dynamical Systems Approach. CinC Li-Wei H. Lehman, Mohammad M. Ghassemi, Jasper Snoek, Shamim Nemati
2015	A*	`conf`	Scalable Bayesian Optimization Using Deep Neural Networks. ICML Jasper Snoek, Oren Rippel, Kevin Swersky, Ryan Kiros, Nadathur Satish, Narayanan Sundaram, Md. Mostofa Ali Patwary, Prabhat, Ryan P. Adams
2015	—	`conf`	Spectral Representations for Convolutional Neural Networks. NIPS Oren Rippel, Jasper Snoek, Ryan P. Adams
2015	J	`jnl`	Spectral Representations for Convolutional Neural Networks. CoRR Oren Rippel, Jasper Snoek, Ryan P. Adams
2014	—	`—`	Bayesian Optimization and Semiparametric Models with Applications to Assistive Technology. Jasper Snoek
2014	A	`conf`	Bayesian Optimization with Unknown Constraints. UAI Michael A. Gelbart, Jasper Snoek, Ryan P. Adams
2014	J	`jnl`	Bayesian Optimization with Unknown Constraints. CoRR Michael A. Gelbart, Jasper Snoek, Ryan P. Adams
2014	J	`jnl`	Data Mining in Bone Marrow Transplant Records to Identify Patients With High Odds of Survival. IEEE J. Biomed. Health Informatics Babak Taati, Jasper Snoek, Dionne M. Aleman, Ardeshir Ghavamzadeh
2014	J	`jnl`	Freeze-Thaw Bayesian Optimization. CoRR Kevin Swersky, Jasper Snoek, Ryan Prescott Adams
2014	—	`conf`	Generalized Linear Models of home activity for automatic detection of mild cognitive impairment in older adults. EMBC Ahmad Akl, Jasper Snoek, Alex Mihailidis
2014	—	`conf`	Global Optimization Approaches for Parameter Tuning in Biomedical Signal Processing: A Focus of Multi-scale Entropy. CinC Mohammad M. Ghassemi, Li-Wei H. Lehman, Jasper Snoek, Shamim Nemati
2014	A*	`conf`	Input Warping for Bayesian Optimization of Non-Stationary Functions. ICML Jasper Snoek, Kevin Swersky, Richard S. Zemel, Ryan P. Adams
2014	J	`jnl`	Input Warping for Bayesian Optimization of Non-stationary Functions. CoRR Jasper Snoek, Kevin Swersky, Richard S. Zemel, Ryan P. Adams
2013	—	`conf`	A Determinantal Point Process Latent Variable Model for Inhibition in Neural Spiking Data. NIPS Jasper Snoek, Richard S. Zemel, Ryan Prescott Adams
2013	—	`conf`	Multi-Task Bayesian Optimization. NIPS Kevin Swersky, Jasper Snoek, Ryan Prescott Adams
2013	J	`jnl`	Video analysis for identifying human operation difficulties and faucet usability assessment. Neurocomputing Babak Taati, Jasper Snoek, Alex Mihailidis
2012	—	`conf`	An Automated Machine Learning Approach Applied to Robotic Stroke Rehabilitation. AAAI Fall Symposium: Artificial Intelligence for Gerontechnology Jasper Snoek, Babak Taati, Alex Mihailidis
2012	J	`jnl`	Nonparametric guidance of autoencoder representations using label information. J. Mach. Learn. Res. Jasper Snoek, Ryan P. Adams, Hugo Larochelle
2012	A	`conf`	On Nonparametric Guidance for Learning Autoencoder Representations. AISTATS Jasper Snoek, Ryan Prescott Adams, Hugo Larochelle
2012	J	`jnl`	Practical Bayesian Optimization of Machine Learning Algorithms CoRR Jasper Snoek, Hugo Larochelle, Ryan Prescott Adams
2012	—	`conf`	Practical Bayesian Optimization of Machine Learning Algorithms. NIPS Jasper Snoek, Hugo Larochelle, Ryan P. Adams
2011	—	`conf`	From Videos to Places: Geolocating the World's Videos. ICDM Workshops Jasper Snoek, Luciano Sbaiz, Hrishikesh B. Aradhye
2011	—	`conf`	Towards Aging-in-Place: Automatic Assessment of Product Usability for Older Adults with Dementia. HISB Babak Taati, Jasper Snoek, Alex Mihailidis
2011	—	`conf`	Towards a single sensor passive solution for automated fall detection. EMBC Michael Belshaw, Babak Taati, Jasper Snoek, Alex Mihailidis
2010	—	`conf`	Automatic segmentation of video to aid the study of faucet usability for older adults. CVPR Workshops Jasper Snoek, Babak Taati, Yulia Eskin, Alex Mihailidis
2010	—	`conf`	Water Flow Detection in a Handwashing Task. CRV Babak Taati, Jasper Snoek, David Giesbrecht, Alex Mihailidis
2009	J	`jnl`	Automated detection of unusual events on stairs. Image Vis. Comput. Jasper Snoek, Jesse Hoey, Liam Stewart, Richard S. Zemel, Alex Mihailidis
2006	—	`conf`	Automated Detection of Unusual Events on Stairs. CRV Jasper Snoek, Jesse Hoey, Liam Stewart, Richard S. Zemel