Jasper Snoek

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

Sebastian Nowozin, Stephan Mandt, Jasper Snoek, 2020, ICML.

Hyperparameter Ensembles for Robustness and Uncertainty Quantification pdf

Jasper Snoek, Dustin Tran, Florian Wenzel, 2020, NeurIPS.

Practical Bayesian Optimization of Machine Learning Algorithms

Jasper Snoek, Ryan P. Adams, Hugo Larochelle, 2012, NIPS.

Opportunity Cost in Bayesian Optimization

Ryan P. Adams, H. Larochelle, Jasper Snoek, 2011 .

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

Michael A. Osborne, F. Hutter, D. Duvenaud, 2014, 1409.4011.

Freeze-Thaw Bayesian Optimization pdf

Jasper Snoek, Ryan P. Adams, Kevin Swersky, 2014, ArXiv.

Scalable Bayesian Optimization Using Deep Neural Networks

Prabhat, Jasper Snoek, Ryan P. Adams, 2015, ICML.

Stochastic Gradient Langevin dynamics that Exploit Neural Network Structure

Jasper Snoek, Roger B. Grosse, David Duvenaud, 2018, ICLR.

Input Warping for Bayesian Optimization of Non-Stationary Functions

Jasper Snoek, Ryan P. Adams, Richard S. Zemel, 2014, ICML.

Bayesian Optimization with Unknown Constraints pdf

Jasper Snoek, Ryan P. Adams, Michael A. Gelbart, 2014, UAI.

Nonparametric guidance of autoencoder representations using label information

Jasper Snoek, Ryan P. Adams, Hugo Larochelle, 2012, J. Mach. Learn. Res..

DPPNet: Approximating Determinantal Point Processes with Deep Networks

Jasper Snoek, Yaniv Ovadia, Zelda Mariet, 2019, NeurIPS.

Winner's Curse? On Pace, Progress, and Empirical Rigor

D. Sculley, Jasper Snoek, Ali Rahimi, 2018, ICLR.

Bayesian Optimization and Semiparametric Models with Applications to Assistive Technology

Jasper Snoek, Jasper Snoek, 2014 .

A Determinantal Point Process Latent Variable Model for Inhibition in Neural Spiking Data

Jasper Snoek, Ryan P. Adams, Richard S. Zemel, 2013, NIPS.

Hydra: Preserving Ensemble Diversity for Model Distillation pdf

Sebastian Nowozin, Jasper Snoek, Tim Salimans, 2020, ArXiv.

O N THE RELATIONSHIP BETWEEN N ORMALISING F LOWS AND V ARIATIONAL-AND D ENOISING A UTOEN-CODERS

Tim Salimans, Jasper Snoek, A. Gritsenko, 2019 .

Automatic Detection of Abnormal Gait on Stairs by Jasper Snoek

Jasper Snoek, 2007 .

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

Joshua V. Dillon, Bastiaan S. Veeling, Tim Salimans, 2020 .

Pre-training helps Bayesian optimization too

George E. Dahl, J. Gilmer, Jasper Snoek, 2022, ArXiv.

On the relationship between Normalising Flows and Variational- and Denoising Autoencoders

Jasper Snoek, Tim Salimans, Alexey A. Gritsenko, 2019, DGS@ICLR.

A Simple Approach to Improve Single-Model Deep Uncertainty via Distance-Awareness

Jasper Snoek, Yeming Wen, Dustin Tran, 2022, 2205.00403.

Validation of the Fracture Mobility Score against the Parker Mobility Score in hip fracture patients.

Jasper Snoek, I. Schipper, D. van der Velde, 2020, Injury.

Opportunity Cost in Bayesian Optimization

Ryan P. Adams, H. Larochelle, Jasper Snoek, 2011 .

Automated detection of falls in the home: Current challenges and future directions

Jasper Snoek, Alex Mihailidis, Babak Taati, 2010 .

On the Parameterization of Gaussian Mean Field Posteriors in Bayesian Neural Networks

Jasper Snoek, Tim Salimans, Stephan Mandt, 2019 .

Assessing the usability of water taps by older adults with dementia

Jennifer Boger, Jasper Snoek, Babak Taati, 2012, Alzheimer's & Dementia.

Textbook process as a composite quality indicator for in-hospital hip fracture care

Jasper Snoek, P. Krijnen, I. Schipper, 2021, Archives of Osteoporosis.

Plex: Towards Reliability using Pretrained Large Model Extensions

Michael W. Dusenberry, Joost R. van Amersfoort, E. Kelly Buchanan, 2022, ArXiv.

Deep Learning for Bayesian Optimization of Scientific Problems with High-Dimensional Structure

Peter Y. Lu, Jasper Snoek, M. Soljavci'c, 2021, 2104.11667.

Pre-trained Gaussian processes for Bayesian optimization

George E. Dahl, J. Gilmer, Jasper Snoek, 2021, 2109.08215.

Deep Learning for Bayesian Optimization of Scientific Problems with High-Dimensional Structure

Peter Y. Lu, Jasper Snoek, M. Soljavci'c, 2021, Trans. Mach. Learn. Res..

A Simple Approach to Improve Single-Model Deep Uncertainty via Distance-Awareness

Jasper Snoek, Yeming Wen, Dustin Tran, 2022, J. Mach. Learn. Res..

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

Bastiaan S. Veeling, Tim Salimans, F. Wenzel, 2020, ICML.

Efficient and Scalable Bayesian Neural Nets with Rank-1 Factors

Michael W. Dusenberry, Jasper Snoek, Yeming Wen, 2020, ICML.

Bad priors, their threats to Bayesian optimization and some remedies via prior learning

George E. Dahl, J. Gilmer, Jasper Snoek, 2022 .

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

Jasper Snoek, George E. Dahl, Kevin Swersky, 2021, ArXiv.

Multi-Task Bayesian Optimization

Jasper Snoek, Ryan P. Adams, Kevin Swersky, 2013, NIPS.

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

Sebastian Nowozin, Jasper Snoek, Jie Ren, 2019, NeurIPS.

Likelihood Ratios for Out-of-Distribution Detection

Jasper Snoek, Jie Ren, Emily Fertig, 2019, NeurIPS.

Pre-trained Gaussian processes for Bayesian optimization

George E. Dahl, J. Gilmer, Jasper Snoek, 2021, 2109.08215.

Second opinion needed: communicating uncertainty in medical machine learning

Jasper Snoek, Benjamin Kompa, Andrew L. Beam, 2021, npj Digital Medicine.

Empirical Frequentist Coverage of Deep Learning Uncertainty Quantification Procedures

Jasper Snoek, Benjamin Kompa, Andrew Beam, 2020, Entropy.

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

Jasper Snoek, Carlos Riquelme, George Tucker, 2018, ICLR.

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

Jasper Snoek, Carlos Riquelme, George Tucker, 2018, ICLR.

Global optimization approaches for parameter tuning in biomedical signal processing: A focus on multi-scale entropy

Shamim Nemati, Jasper Snoek, Li-Wei H. Lehman, 2014, Computing in Cardiology 2014.

Spectral Representations for Convolutional Neural Networks

Jasper Snoek, Ryan P. Adams, Oren Rippel, 2015, NIPS.

Unobtrusive Detection of Mild Cognitive Impairment in Older Adults Through Home Monitoring

Alex Mihailidis, Jasper Snoek, Ahmad Akl, 2017, IEEE Journal of Biomedical and Health Informatics.

Cold Posteriors and Aleatoric Uncertainty pdf

Jasper Snoek, Ben Adlam, Samuel L. Smith, 2020, ArXiv.

Avoiding a Tragedy of the Commons in the Peer Review Process pdf

D. Sculley, Jasper Snoek, Alexander B. Wiltschko, 2018, ArXiv.

Training independent subnetworks for robust prediction pdf

Jasper Snoek, Dustin Tran, Andrew M. Dai, 2020, ICLR.

Evaluating Prediction-Time Batch Normalization for Robustness under Covariate Shift

D. Sculley, Jasper Snoek, Balaji Lakshminarayanan, 2020, ArXiv.

Combining Ensembles and Data Augmentation can Harm your Calibration pdf

Jasper Snoek, Ghassen Jerfel, Dustin Tran, 2020, ICLR.

A Spectral Energy Distance for Parallel Speech Synthesis pdf

Jasper Snoek, Tim Salimans, Nal Kalchbrenner, 2020, NeurIPS.

Automated Detection of Unusual Events on Stairs

Jesse Hoey, Alex Mihailidis, Jasper Snoek, 2006, The 3rd Canadian Conference on Computer and Robot Vision (CRV'06).

Learning Latent Permutations with Gumbel-Sinkhorn Networks pdf

Scott W. Linderman, Jasper Snoek, David Belanger, 2018, ICLR.

Uncertainty Baselines: Benchmarks for Uncertainty & Robustness in Deep Learning

Michael W. Dusenberry, Tim G. J. Rudner, Angelos Filos, 2021, ArXiv.

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

Jasper Snoek, Balaji Lakshminarayanan, Jeremiah Liu, 2020, ArXiv.

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

Jaehoon Lee, Jasper Snoek, Jeffrey Pennington, 2020, ICLR.

The value of case reports in rare oncological scenarios: mixed method analysis of colorectal metastases from breast cancer

Jasper Snoek, P. Bult, I. Nagtegaal, 2023, Clinical & Experimental Metastasis.

Towards a single sensor passive solution for automated fall detection

Alex Mihailidis, Jasper Snoek, Babak Taati, 2011, 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

Faster & More Reliable Tuning of Neural Networks: Bayesian Optimization with Importance Sampling

Jasper Snoek, Ehsan Elhamifar, Jennifer Dy, 2021, AISTATS.

Kernel Regression with Infinite-Width Neural Networks on Millions of Examples

Jasper Snoek, Jaehoon Lee, Zachary Nado, 2023, ArXiv.

Refining the variational posterior through iterative optimization

Jasper Snoek, Dustin Tran, José Miguel Hernández-Lobato, 2019 .

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

Jasper Snoek, Tim Salimans, Stephan Mandt, 2020, ICML.

Sparse MoEs meet Efficient Ensembles

Carlos Riquelme Ruiz, F. Wenzel, Jasper Snoek, 2021, Trans. Mach. Learn. Res..

Sinkhorn Networks: Using Optimal Transport Techniques to Learn Permutations

Jasper Snoek, David Belanger, Gonzalo Mena, 2017 .

On Nonparametric Guidance for Learning Autoencoder Representations

Jasper Snoek, Ryan P. Adams, Hugo Larochelle, 2011, AISTATS.

Multi-Task Bayesian Optimization

Ryan P. Adams, K. Q. Weinberger, L. Bottou, 2013, NIPS.

Beyond Human Data: Scaling Self-Training for Problem-Solving with Language Models

Maxwell L. Bileschi, Hanie Sedghi, Jasper Snoek, 2023, 2312.06585.

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

Bastiaan S. Veeling, Tim Salimans, Kevin Roth, 2020 .

The impact of standardized structured reporting of pathology reports for breast cancer care

Jasper Snoek, S. Siesling, H. V. van Slooten, 2022, Breast.

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

Jasper Snoek, Marin Soljavci'c, Charlotte Loh, 2021, ArXiv.

Video analysis for identifying human operation difficulties and faucet usability assessment

Alex Mihailidis, Jasper Snoek, Babak Taati, 2013, Neurocomputing.

Faster & More Reliable Tuning of Neural Networks: Bayesian Optimization with Importance Sampling

Jennifer G. Dy, Jasper Snoek, Ehsan Elhamifar, 2021, AISTATS.

Deep Uncertainty and the Search for Proteins

Maxwell L. Bileschi, Jasper Snoek, Zelda E. Mariet, 2020 .