Workshop
Gaussian Processes, Spatiotemporal Modeling, and Decision-making Systems
Alexander Terenin · Elizaveta Semenova · Geoff Pleiss · Zi Wang
Room 387
Fri 2 Dec, 7 a.m. PST
In recent years, the growth of decision-making applications, where principled handling of uncertainty is of key concern, has led to increased interest in Bayesian techniques. By offering the capacity to assess and propagate uncertainty in a principled manner, Gaussian processes have become a key technique in areas such as Bayesian optimization, active learning, and probabilistic modeling of dynamical systems. In parallel, the need for uncertainty-aware modeling of quantities that vary over space and time has led to large-scale deployment of Gaussian processes, particularly in application areas such as epidemiology. In this workshop, we bring together researchers from different communities to share ideas and success stories. By showcasing key applied challenges, along with recent theoretical advances, we hope to foster connections and prompt fruitful discussion. We invite researchers to submit extended abstracts for contributed talks and posters.
Schedule
Fri 7:00 a.m. - 7:30 a.m.
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Introduction and Opening Remarks
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Remarks
)
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SlidesLive Video |
🔗 |
Fri 7:30 a.m. - 8:00 a.m.
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Invited Talk: Willie Neiswanger
(
Invited Talk
)
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SlidesLive Video |
Willie Neiswanger 🔗 |
Fri 8:00 a.m. - 8:30 a.m.
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Invited Talk: Marta Blangiardo
(
Invited Talk
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SlidesLive Video |
Marta Blangiardo 🔗 |
Fri 8:30 a.m. - 9:00 a.m.
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Coffee and Discussion
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🔗 |
Fri 9:00 a.m. - 9:30 a.m.
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Invited Talk: Viacheslav Borovitskiy
(
Invited Talk
)
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SlidesLive Video |
Viacheslav Borovitskiy 🔗 |
Fri 9:30 a.m. - 9:45 a.m.
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Multi-Fidelity Experimental Design for Ice-Sheet Simulation
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Contributed Talk
)
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SlidesLive Video |
Pierre Thodoroff 🔗 |
Fri 9:45 a.m. - 10:00 a.m.
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Gaussian Processes at the Helm(holtz): A Better Way to Model Ocean Currents
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Contributed Talk
)
>
SlidesLive Video |
Renato Berlinghieri 🔗 |
Fri 10:00 a.m. - 11:00 a.m.
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Lunch
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🔗 |
Fri 11:00 a.m. - 11:03 a.m.
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Bayesian Spatial Clustered Regression for Count Value Data
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Lightning Talk
)
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SlidesLive Video |
Guanyu Hu 🔗 |
Fri 11:03 a.m. - 11:06 a.m.
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Multi-Mean Gaussian Processes: A novel probabilistic framework for multi-correlated longitudinal data
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Lightning Talk
)
>
SlidesLive Video |
Arthur Leroy 🔗 |
Fri 11:06 a.m. - 11:09 a.m.
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Statistical Downscaling of Sea Surface Temperature Projections with a Multivariate Gaussian Process Model
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Lightning Talk
)
>
SlidesLive Video |
Ayesha Ekanayaka 🔗 |
Fri 11:09 a.m. - 11:12 a.m.
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An Active Learning Reliability Method for Systems with Partially Defined Performance Functions
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Lightning Talk
)
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SlidesLive Video |
Jonathan Sadeghi 🔗 |
Fri 11:12 a.m. - 11:15 a.m.
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Spatiotemporal modeling of European paleoclimate using doubly sparse Gaussian processes
(
Lightning Talk
)
>
SlidesLive Video |
Seth Axen 🔗 |
Fri 11:15 a.m. - 11:18 a.m.
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Towards Improved Learning in Gaussian Processes: The Best of Two Worlds
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Lightning Talk
)
>
SlidesLive Video |
Ke Li 🔗 |
Fri 11:18 a.m. - 11:21 a.m.
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Uncertainty Disentanglement with Non-stationary Heteroscedastic Gaussian Processes for Active Learning
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Lightning Talk
)
>
SlidesLive Video |
Zeel B Patel 🔗 |
Fri 11:21 a.m. - 11:24 a.m.
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Challenges in Gaussian Processes for Non Intrusive Load Monitoring
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Lightning Talk
)
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SlidesLive Video |
Aadesh Desai 🔗 |
Fri 11:24 a.m. - 11:27 a.m.
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Preprocessing Data of Varying Trial Duration with Linear Time Warping to Extend on the Applicability of SNP-GPFA
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Lightning Talk
)
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SlidesLive Video |
Arjan Dhesi 🔗 |
Fri 11:27 a.m. - 11:30 a.m.
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Non-Gaussian Process Regression
(
Lightning Talk
)
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SlidesLive Video |
Yaman Kindap 🔗 |
Fri 11:30 a.m. - 12:00 p.m.
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Invited Talk: Jasper Snoek
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Invited Talk
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SlidesLive Video |
Jasper Snoek 🔗 |
Fri 12:00 p.m. - 12:15 p.m.
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Surrogate-Assisted Evolutionary Multi-Objective Optimization for Hardware Design Space Exploration
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Contributed Talk
)
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SlidesLive Video |
Renzhi Chen 🔗 |
Fri 12:15 p.m. - 12:45 p.m.
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Coffee and Discussion
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🔗 |
Fri 12:45 p.m. - 1:15 p.m.
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Invited Talk: Paula Moraga
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Invited Talk
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SlidesLive Video |
Paula Moraga 🔗 |
Fri 1:15 p.m. - 1:30 p.m.
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Sparse Bayesian Optimization
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Contributed Talk
)
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SlidesLive Video |
Sulin Liu 🔗 |
Fri 1:30 p.m. - 1:45 p.m.
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Constraining Gaussian Processes to Systems of Linear Ordinary Differential Equations
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Contributed Talk
)
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SlidesLive Video |
Andreas Besginow 🔗 |
Fri 1:45 p.m. - 2:45 p.m.
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Poster Session
(
Poster Session
)
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🔗 |
Fri 2:45 p.m. - 3:15 p.m.
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Invited Talk: Carolina Osorio
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Invited Talk
)
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SlidesLive Video |
Carolina Osorio 🔗 |
Fri 3:15 p.m. - 3:55 p.m.
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Panel Discussion
(
Panel
)
>
SlidesLive Video |
Jacob Gardner · Marta Blangiardo · Viacheslav Borovitskiy · Jasper Snoek · Paula Moraga · Carolina Osorio 🔗 |
Fri 3:55 p.m. - 4:00 p.m.
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Closing Remarks
(
Remarks
)
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🔗 |
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Spatiotemporal modeling of European paleoclimate using doubly sparse Gaussian processes
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Poster
)
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Seth Axen · Alexandra Gessner · Christian Sommer · Nils Weitzel · Álvaro Tejero-Cantero 🔗 |
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Identifying latent climate signals using sparse hierarchical Gaussian processes
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Poster
)
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Matt Amos · Thomas Pinder · Paul Young 🔗 |
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c-TPE: Generalizing Tree-structured Parzen Estimator with Inequality Constraints for Continuous and Categorical Hyperparameter Optimization
(
Poster
)
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Shuhei Watanabe · Frank Hutter 🔗 |
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Preferential Bayesian Optimization with Hallucination Believer
(
Poster
)
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Shion Takeno · Masahiro Nomura · Masayuki Karasuyama 🔗 |
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Symbolic-Model-Based Reinforcement Learning
(
Poster
)
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Pierre-alexandre Kamienny · Sylvain Lamprier 🔗 |
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An Active Learning Reliability Method for Systems with Partially Defined Performance Functions
(
Poster
)
>
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Jonathan Sadeghi · Romain Mueller · John Redford 🔗 |
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Multi-fidelity Bayesian experimental design using power posteriors
(
Poster
)
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Andrew Jones · Diana Cai · Barbara Engelhardt 🔗 |
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Bayesian Sequential Experimental Design for a Partially Linear Model with a Gaussian Process Prior
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Poster
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Shunsuke Horii 🔗 |
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Fantasizing with Dual GPs in Bayesian Optimization and Active Learning
(
Poster
)
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Paul Chang · Prakhar Verma · ST John · Victor Picheny · Henry Moss · Arno Solin 🔗 |
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Deep Gaussian Process-based Multi-fidelity Bayesian Optimization for Simulated Chemical Reactors
(
Poster
)
>
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Tom Savage · Nausheen Basha · Omar Matar · Antonio del Rio Chanona 🔗 |
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Ice Core Dating using Probabilistic Programming
(
Poster
)
>
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Aditya Ravuri · Tom Andersson · Ieva Kazlauskaite · William Tebbutt · Richard Turner · Scott Hosking · Neil Lawrence · Markus Kaiser 🔗 |
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Scalable Gaussian Process Hyperparameter Optimization via Coverage Regularization
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Poster
)
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Killian Wood · Alec Dunton · Amanda Muyskens · Benjamin Priest 🔗 |
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Integrated Fourier Features for Fast Sparse Variational Gaussian Process Regression
(
Poster
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Talay Cheema 🔗 |
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Provably Reliable Large-Scale Sampling from Gaussian Processes
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Poster
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Anthony Stephenson · Robert Allison 🔗 |
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Uncovering the short-time dynamics of electricity day-ahead markets
(
Poster
)
>
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Antonio Malpica-Morales · S KALLIADASIS · Miguel Durán Olivencia 🔗 |
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Distributionally Robust Bayesian Optimization with φ-divergences
(
Poster
)
>
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Hisham Husain · Vu Nguyen · Anton van den Hengel 🔗 |
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Towards Improved Learning in Gaussian Processes: The Best of Two Worlds
(
Poster
)
>
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Rui Li · ST John · Arno Solin 🔗 |
-
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HyperBO+: Pre-training a universal hierarchical Gaussian process prior for Bayesian optimization
(
Poster
)
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Zhou Fan · Xinran Han · Zi Wang 🔗 |
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Sequential Gaussian Processes for Online Learning of Nonstationary Functions
(
Poster
)
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Michael Minyi Zhang · Bianca Dumitrascu · Sinead Williamson · Barbara Engelhardt 🔗 |
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Gaussian Process Thompson sampling for Bayesian optimization of dynamic masking-based language model pre-training
(
Poster
)
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Iñigo Urteaga · Moulay Zaidane Draidia · Tomer Lancewicki · Shahram Khadivi 🔗 |
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Gaussian Process Regression for In-vehicle Disconnect Clutch Transfer Function Development
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Poster
)
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Huanyi Shui · Yijing Zhang · Deepthi Antony · devesh upadhyay · James McCallum · Yuji Fujii · Edward Dai 🔗 |
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Variational Inference for Extreme Spatio-Temporal Matrix Completion
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Poster
)
>
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Charul Charul · Pravesh Biyani 🔗 |
-
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Preprocessing Data of Varying Trial Duration with Linear Time Warping to Extend on the Applicability of SNP-GPFA
(
Poster
)
>
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Arjan Dhesi · Arno Onken 🔗 |
-
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Are All Training Data Useful? A Empirical Revisit of Subset Selection in Bayesian Optimization
(
Poster
)
>
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Peili Mao · Ke Li 🔗 |
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Non-Gaussian Process Regression
(
Poster
)
>
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Yaman Kindap · Simon Godsill 🔗 |
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Bayesian Spatial Clustered Regression for Count Value Data
(
Poster
)
>
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Peng Zhao · Hou-Cheng Yang · Dipak Dey · Guanyu Hu 🔗 |
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Efficient Variational Gaussian Processes Initialization via Kernel-based Least Squares Fitting
(
Poster
)
>
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Xinran Zhu · David Bindel · Jacob Gardner 🔗 |
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Variational Bayesian Inference and Learning for Continuous Switching Linear Dynamical Systems
(
Poster
)
>
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Jack Goffinet · David Carlson 🔗 |
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Adaptive Experimentation at Scale
(
Poster
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Ethan Che · Hongseok Namkoong 🔗 |
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Preference-Aware Constrained Multi-Objective Bayesian Optimization
(
Poster
)
>
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Alaleh Ahmadianshalchi · Syrine Belakaria · Janardhan Rao Doppa 🔗 |
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Imputation and forecasting for Multi-Output Gaussian Process in Smart Grid
(
Poster
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JIANGJIAO XU · Ke Li 🔗 |
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Shaping of Magnetic Field Coils in Fusion Reactors using Bayesian Optimisation
(
Poster
)
>
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Timothy Nunn · Vignesh Gopakumar · Sebastien Kahn 🔗 |
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Joint Point Process Model for Counterfactual Treatment--Outcome Trajectories Under Policy Interventions
(
Poster
)
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Çağlar Hızlı · ST John · Anne Juuti · Tuure Saarinen · Kirsi Pietiläinen · Pekka Marttinen 🔗 |
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PI is back! Switching Acquisition Functions in Bayesian Optimization
(
Poster
)
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Carolin Benjamins · Elena Raponi · Anja Jankovic · Koen van der Blom · Maria Laura Santoni · Marius Lindauer · Carola Doerr 🔗 |
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Actually Sparse Variational Gaussian Processes
(
Poster
)
>
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Jake Cunningham · So Takao · Mark van der Wilk · Marc Deisenroth 🔗 |
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Predicting Spatiotemporal Counts of Opioid-related Fatal Overdoses via Zero-Inflated Gaussian Processes
(
Poster
)
>
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Kyle Heuton · Shikhar Shrestha · Thomas Stopka · Jennifer Pustz · · Michael Hughes 🔗 |
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Expert Selection in Distributed Gaussian Processes: A Multi-label Classification Approach
(
Poster
)
>
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Hamed Jalali · Gjergji Kasneci 🔗 |
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Statistical Downscaling of Sea Surface Temperature Projections with a Multivariate Gaussian Process Model
(
Poster
)
>
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Ayesha Ekanayaka · Emily Kang · Peter Kalmus · Amy Braverman 🔗 |
-
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Multi-Mean Gaussian Processes: A novel probabilistic framework for multi-correlated longitudinal data
(
Poster
)
>
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Arthur Leroy · Mauricio A Álvarez 🔗 |
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Spatiotemporal Residual Regularization with Kronecker Product Structure for Traffic Forecasting
(
Poster
)
>
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Seongjin Choi · Nicolas Saunier · Martin Trepanier · Lijun Sun 🔗 |
-
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Uncertainty Disentanglement with Non-stationary Heteroscedastic Gaussian Processes for Active Learning
(
Poster
)
>
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Zeel B Patel · Nipun Batra · Kevin Murphy 🔗 |
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Active Learning with Convolutional Gaussian Neural Processes for Environmental Sensor Placement
(
Poster
)
>
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Tom Andersson · Wessel Bruinsma · Efstratios Markou · Daniel C. Jones · Scott Hosking · James Requeima · Anna Vaughan · Anna-Louise Ellis · Matthew Lazzara · Richard Turner 🔗 |
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Random Features Approximation for Fast Data-Driven Control
(
Poster
)
>
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Kimia Kazemian · Sarah Dean 🔗 |
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Deep Mahalanobis Gaussian Process
(
Poster
)
>
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Daniel Augusto de Souza · Diego Mesquita · César Lincoln Mattos · João Paulo Gomes 🔗 |
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An Empirical Analysis of the Advantages of Finite vs.~Infinite Width Bayesian Neural Networks
(
Poster
)
>
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Jiayu Yao · Yaniv Yacoby · Beau Coker · Weiwei Pan · Finale Doshi-Velez 🔗 |
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Non-exchangeability in Infinite Switching Linear Dynamical Systems
(
Poster
)
>
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Victor Geadah · Jonathan Pillow 🔗 |
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Posterior Consistency for Gaussian Process Surrogate Models with Generalized Observations
(
Poster
)
>
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Rujian Chen · John Fisher III 🔗 |
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Recommendations for Baselines and Benchmarking Approximate Gaussian Processes
(
Poster
)
>
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Sebastian Ober · David Burt · Artem Artemev · Mark van der Wilk 🔗 |
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Challenges in Gaussian Processes for Non Intrusive Load Monitoring
(
Poster
)
>
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Aadesh Desai · Gautam Vashishtha · Zeel B Patel · Nipun Batra 🔗 |
-
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Multi-fidelity experimental design for ice-sheet simulation
(
Poster
)
>
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Pierre Thodoroff · Markus Kaiser · Rosie Williams · Robert Arthern · Scott Hosking · Neil Lawrence · Ieva Kazlauskaite 🔗 |
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Sparse Bayesian Optimization
(
Poster
)
>
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Sulin Liu · Qing Feng · David Eriksson · Ben Letham · Eytan Bakshy 🔗 |
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Gaussian processes at the Helm(holtz): A better way to model ocean currents
(
Poster
)
>
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Renato Berlinghieri · Tamara Broderick · Ryan Giordano · Tamay Ozgokmen · Kaushik Srinivasan · Brian Trippe · Junfei Xia 🔗 |
-
|
Surrogate-Assisted Evolutionary Multi-Objective Optimization for Hardware Design Space Exploration
(
Poster
)
>
|
Renzhi Chen · Ke Li 🔗 |
-
|
Constraining Gaussian Processes to Systems of Linear Ordinary Differential Equations
(
Poster
)
>
|
Andreas Besginow · Markus Lange-Hegermann 🔗 |