40 Results

Tutorial
Mon 8:00 Bayesian Deep Learning and a Probabilistic Perspective of Model Construction
Andrew Wilson
Poster
Tue 7:00 Bayesian Optimisation over Multiple Continuous and Categorical Inputs
Robin Ru, Ahsan Alvi, Vu Nguyen, Michael A Osborne, Stephen Roberts
Poster
Tue 8:00 Parametric Gaussian Process Regressors
Martin Jankowiak, Geoff Pleiss, Jacob Gardner
Poster
Tue 9:00 Disentangling Trainability and Generalization in Deep Neural Networks
Lechao Xiao, Jeffrey Pennington, Samuel Schoenholz
Poster
Tue 10:00 Differentiable Likelihoods for Fast Inversion of 'Likelihood-Free' Dynamical Systems
Hans Kersting, Nicholas Krämer, Martin Schiegg, Christian Daniel, Michael Schober, Philipp Hennig
Poster
Tue 11:00 Near-linear time Gaussian process optimization with adaptive batching and resparsification
Daniele Calandriello, Luigi Carratino, Alessandro Lazaric, Michal Valko, Lorenzo Rosasco
Poster
Tue 14:00 Infinite attention: NNGP and NTK for deep attention networks
Jiri Hron, Yasaman Bahri, Jascha Sohl-Dickstein, Roman Novak
Poster
Tue 14:00 Knowing The What But Not The Where in Bayesian Optimization
Vu Nguyen, Michael A Osborne
Poster
Tue 18:00 Multi-fidelity Bayesian Optimization with Max-value Entropy Search and its Parallelization
Shion Takeno, Hitoshi Fukuoka, Yuhki Tsukada, Toshiyuki Koyama, Motoki Shiga, Ichiro Takeuchi, Masayuki Karasuyama
Poster
Wed 5:00 Efficient Non-conjugate Gaussian Process Factor Models for Spike Count Data using Polynomial Approximations
Stephen Keeley, David Zoltowski, Yiyi Yu, Spencer Smith, Jonathan Pillow
Poster
Wed 8:00 Randomly Projected Additive Gaussian Processes for Regression
Ian Delbridge, dbindel S Bindel, Andrew Wilson
Poster
Wed 8:00 Private Outsourced Bayesian Optimization
Dmitrii Kharkovskii, Zhongxiang Dai, Bryan Kian Hsiang Low
Poster
Wed 8:00 Self-Modulating Nonparametric Event-Tensor Factorization
Zheng Wang, Xinqi Chu, Shandian Zhe
Poster
Wed 8:00 Stochastic Gradient and Langevin Processes
Xiang Cheng, Dong Yin, Peter Bartlett, Michael Jordan
Poster
Wed 11:00 Deep Gaussian Markov Random Fields
Per Sidén, Fredrik Lindsten
Poster
Wed 12:00 Implicit Regularization of Random Feature Models
Arthur Jacot, Berfin Simsek, Francesco Spadaro, Clement Hongler, Franck Gabriel
Poster
Wed 12:00 Scalable Exact Inference in Multi-Output Gaussian Processes
Wessel Bruinsma, Eric Perim Martins, William Tebbutt, Scott Hosking, Arno Solin, Richard E Turner
Poster
Wed 13:00 Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances
Csaba Toth, Harald Oberhauser
Poster
Wed 13:00 State Space Expectation Propagation: Efficient Inference Schemes for Temporal Gaussian Processes
William Wilkinson, Paul Chang, Michael Andersen, Arno Solin
Poster
Wed 14:00 Healing Products of Gaussian Process Experts
samuel cohen, Rendani Mbuvha, Tshilidzi Marwala, Marc Deisenroth
Poster
Wed 14:00 Sparse Gaussian Processes with Spherical Harmonic Features
Vincent Dutordoir, Nicolas Durrande, James Hensman
Poster
Wed 16:00 Non-separable Non-stationary random fields
Kangrui Wang, Ollie Hamelijnck, Theo Damoulas, Mark Steel
Poster
Thu 6:00 BINOCULARS for efficient, nonmyopic sequential experimental design
Shali Jiang, Henry Chai, Javier Gonzalez, Roman Garnett
Poster
Thu 6:00 Causal Inference using Gaussian Processes with Structured Latent Confounders
Sam Witty, Kenta Takatsu, David Jensen, Vikash Mansinghka
Poster
Thu 6:00 Spectrum Dependent Learning Curves in Kernel Regression and Wide Neural Networks
Blake Bordelon, Abdul Canatar, Cengiz Pehlevan
Poster
Thu 7:00 R2-B2: Recursive Reasoning-Based Bayesian Optimization for No-Regret Learning in Games
Zhongxiang Dai, Yizhou Chen, Bryan Kian Hsiang Low, Patrick Jaillet , Teck-Hua Ho
Poster
Thu 12:00 Inter-domain Deep Gaussian Processes
Tim G. J. Rudner, Dino Sejdinovic, Yarin Gal
Poster
Thu 13:00 Stochastic Differential Equations with Variational Wishart Diffusions
Martin Jørgensen, Marc Deisenroth, Hugh Salimbeni
Poster
Thu 13:00 A quantile-based approach for hyperparameter transfer learning
David Salinas, Huibin Shen, Valerio Perrone
Poster
Thu 13:00 Projective Preferential Bayesian Optimization
Petrus Mikkola, Milica Todorović, Jari Järvi, Patrick Rinke, Samuel Kaski
Poster
Thu 13:00 Modulating Surrogates for Bayesian Optimization
Erik Bodin, Markus Kaiser, Ieva Kazlauskaite, Zhenwen Dai, Neill Campbell, Carl Henrik Ek
Poster
Thu 13:00 Influenza Forecasting Framework based on Gaussian Processes
Christoph Zimmer, Reza Yaesoubi
Poster
Thu 14:00 Scalable Gaussian Process Separation for Kernels with a Non-Stationary Phase
Jan Graßhoff, Alexandra Jankowski, Philipp Rostalski
Poster
Thu 14:00 Efficiently sampling functions from Gaussian process posteriors
James Wilson, Slava Borovitskiy, Alexander Terenin, Peter Mostowsky, Marc Deisenroth
Poster
Thu 17:00 Multi-objective Bayesian Optimization using Pareto-frontier Entropy
Shinya Suzuki, Shion Takeno, Tomoyuki Tamura, Kazuki Shitara, Masayuki Karasuyama
Workshop
Fri 9:00 Poster Session (click to see links)
Workshop
Sat 11:45 "Uncertainty Quantification Using Martingales for Misspecified Gaussian Processes"
Aaditya Ramdas
Workshop
(#50 / Sess. 1) Graph Convolutional Gaussian Processes for Link Prediction
Felix Opolka
Workshop
Variational Auto-Regressive Gaussian Processes for Continual Learning
Workshop
Online Inducing Points Selection for Gaussian Processes