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Affinity Workshop
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Mon 8:55 |
Computation of Discrete Flows Over Networks via Constrained Wasserstein Barycenters Ferran Arque, Cesar Uribe |
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Spotlight
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Wed 7:30 |
Bayesian Optimistic Optimisation with Exponentially Decaying Regret Hung Tran-The, Sunil Gupta, Santu Rana, Svetha Venkatesh |
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Poster
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Wed 9:00 |
Bayesian Optimistic Optimisation with Exponentially Decaying Regret Hung Tran-The, Sunil Gupta, Santu Rana, Svetha Venkatesh |
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Spotlight
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Wed 18:20 |
Gaussian Process-Based Real-Time Learning for Safety Critical Applications Armin Lederer, Alejandro Ordóñez Conejo, Korbinian Maier, Wenxin Xiao, Jonas Umlauft, Sandra Hirche |
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Poster
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Wed 21:00 |
Gaussian Process-Based Real-Time Learning for Safety Critical Applications Armin Lederer, Alejandro Ordóñez Conejo, Korbinian Maier, Wenxin Xiao, Jonas Umlauft, Sandra Hirche |
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Oral
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Thu 5:00 |
Tighter Bounds on the Log Marginal Likelihood of Gaussian Process Regression Using Conjugate Gradients Artem Artemev, David Burt, Mark van der Wilk |
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Spotlight
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Thu 5:20 |
Isometric Gaussian Process Latent Variable Model for Dissimilarity Data Martin Jørgensen, Søren Hauberg |
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Spotlight
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Thu 5:25 |
Variational Auto-Regressive Gaussian Processes for Continual Learning Sanyam Kapoor, Theofanis Karaletsos, Thang Bui |
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Spotlight
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Thu 5:30 |
Sparse within Sparse Gaussian Processes using Neighbor Information Gia-Lac Tran, Dimitrios Milios, Pietro Michiardi, Maurizio Filippone |
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Spotlight
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Thu 5:35 |
SigGPDE: Scaling Sparse Gaussian Processes on Sequential Data Maud Lemercier, Cristopher Salvi, Thomas Cass, Edwin V Bonilla, Theo Damoulas, Terry Lyons |
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Spotlight
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Thu 5:40 |
On Signal-to-Noise Ratio Issues in Variational Inference for Deep Gaussian Processes Tim G. J. Rudner, Oscar Key, Yarin Gal, Tom Rainforth |
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Spotlight
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Thu 5:45 |
Scalable Variational Gaussian Processes via Harmonic Kernel Decomposition Shengyang Sun, Jiaxin Shi, Andrew Wilson, Roger Grosse |
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Spotlight
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Thu 6:20 |
Beyond the Pareto Efficient Frontier: Constraint Active Search for Multiobjective Experimental Design Gustavo Malkomes, Harvey Cheng, Eric Lee, Michael McCourt |
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Spotlight
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Thu 7:40 |
Bayesian Quadrature on Riemannian Data Manifolds Christian Fröhlich, Alexandra Gessner, Philipp Hennig, Bernhard Schölkopf, Georgios Arvanitidis |
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Poster
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Thu 9:00 |
Beyond the Pareto Efficient Frontier: Constraint Active Search for Multiobjective Experimental Design Gustavo Malkomes, Harvey Cheng, Eric Lee, Michael McCourt |
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Poster
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Thu 9:00 |
Isometric Gaussian Process Latent Variable Model for Dissimilarity Data Martin Jørgensen, Søren Hauberg |
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Poster
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Thu 9:00 |
Variational Auto-Regressive Gaussian Processes for Continual Learning Sanyam Kapoor, Theofanis Karaletsos, Thang Bui |
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Poster
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Thu 9:00 |
Tighter Bounds on the Log Marginal Likelihood of Gaussian Process Regression Using Conjugate Gradients Artem Artemev, David Burt, Mark van der Wilk |
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Poster
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Thu 9:00 |
Sparse within Sparse Gaussian Processes using Neighbor Information Gia-Lac Tran, Dimitrios Milios, Pietro Michiardi, Maurizio Filippone |
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Poster
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Thu 9:00 |
SigGPDE: Scaling Sparse Gaussian Processes on Sequential Data Maud Lemercier, Cristopher Salvi, Thomas Cass, Edwin V Bonilla, Theo Damoulas, Terry Lyons |
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Poster
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Thu 9:00 |
Bayesian Quadrature on Riemannian Data Manifolds Christian Fröhlich, Alexandra Gessner, Philipp Hennig, Bernhard Schölkopf, Georgios Arvanitidis |
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Poster
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Thu 9:00 |
On Signal-to-Noise Ratio Issues in Variational Inference for Deep Gaussian Processes Tim G. J. Rudner, Oscar Key, Yarin Gal, Tom Rainforth |
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Poster
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Thu 9:00 |
Scalable Variational Gaussian Processes via Harmonic Kernel Decomposition Shengyang Sun, Jiaxin Shi, Andrew Wilson, Roger Grosse |
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Spotlight
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Thu 17:20 |
Objective Bound Conditional Gaussian Process for Bayesian Optimization Taewon Jeong, Heeyoung Kim |
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Spotlight
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Thu 17:35 |
Bias-Free Scalable Gaussian Processes via Randomized Truncations Andres Potapczynski, Luhuan Wu, Dan Biderman, Geoff Pleiss, John Cunningham |
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Oral
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Thu 19:20 |
SKIing on Simplices: Kernel Interpolation on the Permutohedral Lattice for Scalable Gaussian Processes Sanyam Kapoor, Marc Finzi, Ke Alexander Wang, Andrew Wilson |
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Spotlight
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Thu 20:30 |
Lenient Regret and Good-Action Identification in Gaussian Process Bandits Xu Cai, Selwyn Gomes, Jonathan Scarlett |
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Spotlight
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Thu 20:35 |
Equivariant Learning of Stochastic Fields: Gaussian Processes and Steerable Conditional Neural Processes Peter Holderrieth, Michael Hutchinson, Yee-Whye Teh |
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Spotlight
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Thu 20:40 |
Value-at-Risk Optimization with Gaussian Processes Quoc Phong Nguyen, Zhongxiang Dai, Bryan Kian Hsiang Low, Patrick Jaillet |
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Spotlight
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Thu 20:45 |
High-Dimensional Gaussian Process Inference with Derivatives Filip de Roos, Alexandra Gessner, Philipp Hennig |
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Spotlight
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Thu 20:50 |
GP-Tree: A Gaussian Process Classifier for Few-Shot Incremental Learning Idan Achituve, Aviv Navon, Yochai Yemini, Gal Chechik, Ethan Fetaya |
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Poster
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Thu 21:00 |
GP-Tree: A Gaussian Process Classifier for Few-Shot Incremental Learning Idan Achituve, Aviv Navon, Yochai Yemini, Gal Chechik, Ethan Fetaya |
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Poster
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Thu 21:00 |
Lenient Regret and Good-Action Identification in Gaussian Process Bandits Xu Cai, Selwyn Gomes, Jonathan Scarlett |
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Poster
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Thu 21:00 |
Objective Bound Conditional Gaussian Process for Bayesian Optimization Taewon Jeong, Heeyoung Kim |
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Poster
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Thu 21:00 |
Equivariant Learning of Stochastic Fields: Gaussian Processes and Steerable Conditional Neural Processes Peter Holderrieth, Michael Hutchinson, Yee-Whye Teh |
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Poster
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Thu 21:00 |
SKIing on Simplices: Kernel Interpolation on the Permutohedral Lattice for Scalable Gaussian Processes Sanyam Kapoor, Marc Finzi, Ke Alexander Wang, Andrew Wilson |
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Poster
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Thu 21:00 |
High-Dimensional Gaussian Process Inference with Derivatives Filip de Roos, Alexandra Gessner, Philipp Hennig |
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Poster
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Thu 21:00 |
Bias-Free Scalable Gaussian Processes via Randomized Truncations Andres Potapczynski, Luhuan Wu, Dan Biderman, Geoff Pleiss, John Cunningham |
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Poster
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Thu 21:00 |
Value-at-Risk Optimization with Gaussian Processes Quoc Phong Nguyen, Zhongxiang Dai, Bryan Kian Hsiang Low, Patrick Jaillet |
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Workshop
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Sat 12:23 |
Selective Focusing Learning in Conditional GANs Kyeongbo Kong, Kyunghun Kim, Woo-jin Song, Suk-Ju Kang |
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Workshop
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Examining the Human Perceptibility of Black-Box Adversarial Attacks on Face Recognition Benjamin Spetter-Goldstein, Nataniel Ruiz, Sarah Bargal |
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Workshop
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A unified PAC-Bayesian framework for machine unlearning via information risk minimization Sharu Jose, Osvaldo Simeone |
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Workshop
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Counterfactual Explanations for Graph Neural Networks Ana Lucic, Maartje ter Hoeve, Gabriele Tolomei, Maarten de Rijke, Fabrizio Silvestri |
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Workshop
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Increasing Depth Leads to U-Shaped Test Risk in Over-parameterized Convolutional Networks Eshaan Nichani, Adit Radhakrishnan, Caroline Uhler |
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Workshop
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Selective Focusing Learning in Conditional GANs Kyeongbo Kong, Kyunghun Kim, Woo-jin Song, Suk-Ju Kang |