NeurIPS Workshop on Gaussian Processes, Spatiotemporal Modeling, and Decision-making Systems

December 2nd, 2022


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.


Time (USA) Event
09:00 - 09:30 Introduction and Opening Remarks
09:30 - 10:00 Invited Talk: Willie Neiswanger
10:00 - 10:30 Invited Talk: Marta Blangiardo
10:30 - 11:00 Coffee and Discussion
11:00 - 11:30 Invited Talk: Viacheslav Borovitskiy
11:30 - 11:45 Contributed Talk: Pierre Thodoroff
11:45 - 12:00 Contributed Talk: Renato Berlinghieri
12:00 - 13:00 Lunch
13:00 - 13:30 Lightning Talks
13:30 - 14:00 Invited Talk: Jasper Snoek
14:00 - 14:15 Contributed Talk: Renzhi Chen
14:15 - 14:45 Coffee and Discussion
14:45 - 15:15 Invited Talk: Paula Moraga
15:15 - 15:30 Contributed Talk: Sulin Liu
15:30 - 15:45 Contributed Talk: Andreas Besginow
15:45 - 16:45 Poster Session
16:45 - 17:15 Invited Talk: Carolina Osorio
17:15 - 17:55 Panel Discussion
17:55 - 18:00 Closing Remarks

Accepted Workshop Papers

Title Authors
Spatiotemporal modeling of European paleoclimate using doubly sparse Gaussian processes
paper poster
Seth D Axen (Machine Learning ⇌ Science Colaboratory); Alexandra Gessner (University of Tübingen); Christian Sommer (Heidelberg Academy of Sciences and Humanities); Nils Weitzel (University of Tübingen); Alvaro Tejero-Cantero (University of Tübingen)
Identifying latent climate signals using sparse hierarchical Gaussian processes
Matt Amos (Lancaster University); Thomas Pinder (Lancaster University); Paul Young (Lancaster University)
Multi-fidelity experimental design for ice-sheet simulation
Pierre Thodoroff (University of Cambridge); Markus Kaiser (University of Cambridge); Rosie  Williams (British Antarctic Survey); Robert Arthern (British Antarctic Survey); Scott Hosking (British Antarctic Survey); Neil D Lawrence (University of Cambridge); Ieva Kazlauskaite (University of Cambridge)
c-TPE: Generalizing Tree-structured Parzen Estimator with Inequality Constraints for Continuous and Categorical Hyperparameter Optimization
paper poster
Shuhei Watanabe (University of Freiburg); Frank Hutter (University of Freiburg)
Preferential Bayesian Optimization with Hallucination Believer
paper poster
Shion Takeno (Nagoya Institute of Technology); Masahiro Nomura (CyberAgent, Inc.); Masayuki Karasuyama (Nagoya Institute of Technology)
Symbolic-Model-Based Reinforcement Learning
paper poster
Pierre-Alexandre Kamienny (Facebook AI Research); Sylvain Lamprier (ISIR-SU)
An Active Learning Reliability Method for Systems with Partially Defined Performance Functions
paper poster
Jonathan C Sadeghi (Five AI Ltd); Romain Mueller (; John Redford (Five AI Ltd.)
Multi-fidelity Bayesian experimental design using power posteriors
Andrew Jones (Princeton University Department of Computer Science); Diana Cai (Princeton University); Barbara Engelhardt (Princeton University)
Bayesian Sequential Experimental Design for a Partially Linear Model with a Gaussian Process Prior
Shunsuke Horii (Waseda University)
Fantasizing with Dual GPs in Bayesian Optimization and Active Learning
paper poster
Paul Chang (Aalto University); Prakhar Verma (Aalto University); ST John (Aalto University & Finnish Center for Artificial Intelligence); Victor Picheny (Prowler); Henry B Moss (Secondmind); Arno Solin (Aalto University)
Deep Gaussian Process-based Multi-fidelity Bayesian Optimization for Simulated Chemical Reactors
paper poster
Tom Savage (Imperial College London); Nausheen Basha (Imperial College London); Omar Matar (Imperial College London); Antonio del Rio Chanona (Imperial College London)
Ice Core Dating using Probabilistic Programming
Aditya Ravuri (University of Cambridge); Tom Andersson (British Antarctic Survey); Ieva Kazlauskaite (University of Cambridge); William Tebbutt (University of Cambridge); Richard E. Turner (University of Cambridge); Scott Hosking (British Antarctic Survey); Neil D Lawrence (University of Cambridge); Markus Kaiser (University of Cambridge)
Scalable Gaussian Process Hyperparameter Optimization via Coverage Regularization
paper poster
Killian R Wood (University of Colorado, Boulder); Alec  M Dunton (Lawrence Livermore National Labs); Amanda L Muyskens (Lawrence Livermore National Laboratory); Benjamin Priest (Lawrence Livermore National Laboratory)
Integrated Fourier Features for Fast Sparse Variational Gaussian Process Regression
paper poster
Talay M Cheema (University of Cambridge)
Provably Reliable Large-Scale Sampling from Gaussian Processes
paper poster
Anthony Stephenson (University of Bristol); Robert Allison (University of Bristol)
Uncovering the short-time dynamics of electricity day-ahead markets
paper poster
Antonio Malpica Morales (Imperial College London); Serafim Kalliadasis (Imperial College London); Miguel Durán Olivencia (Imperial College London)
Distributionally Robust Bayesian Optimization with φ-divergences
paper poster
Hisham Husain (Amazon); Vu Nguyen (Amazon); Anton van den Hengel (University of Adelaide)
Sparse Bayesian Optimization
paper poster
Sulin Liu (Princeton University); Qing Feng (Facebook); David Eriksson (Meta); Benjamin Letham (Facebook); Eytan Bakshy (Meta)
Gaussian processes at the Helm(holtz): A better way to model ocean currents
paper poster
Renato Berlinghieri (MIT); Tamara Broderick (MIT); Ryan Giordano (MIT); Tamay Ozgokmen (University of Miami); Kaushik Srinivasan (UCLA); Brian L Trippe (MIT); Junfei Xia (University of Miami)
Towards Improved Learning in Gaussian Processes: The Best of Two Worlds
paper poster
Rui Li (Aalto University); ST John (Aalto University); Arno Solin (Aalto University)
HyperBO+: Pre-training a universal hierarchical Gaussian process prior for Bayesian optimization
paper poster
Zhou Fan (Harvard University); Xinran Han (Harvard University); Zi Wang (Google)
Sequential Gaussian Processes for Online Learning of Nonstationary Functions
Michael Zhang (University of Hong Kong); Bianca  M Dumitrascu (Princeton  University); Sinead A Williamson (UT Austin); Barbara Engelhardt (Princeton University)
Gaussian Process Thompson sampling for Bayesian optimization of dynamic masking-based language model pre-training
paper poster
Iñigo Urteaga (Columbia University); Moulay Zaidane Draidia (Columbia University); Tomer Lancewicki (Walmart Global Tech); Shahram Khadivi (eBay, Inc.)
Gaussian Process Regression for In-vehicle Disconnect Clutch Transfer Function Development
paper poster
Huanyi Shui (Ford Motor Co.); Yijing Zhang (Ford Motor Co.); Deepthi Antony (Ford Motor Co.); Devesh Upadhyay (Ford Motor Co.); James McCallum (Ford Motor Co.); Yuji Fujii (Ford Motor Co.); Edward Dai (Ford Motor Co.)
Variational Inference for Extreme Spatio-Temporal Matrix Completion
paper poster
Charul Paliwal (IIIT Delhi); Pravesh Biyani (IIIT Delhi)
Preprocessing Data of Varying Trial Duration with Linear Time Warping to Extend on the Applicability of SNP-GPFA
paper poster
Arjan Dhesi (University of Edinburgh); Arno Onken (University of Edinburgh)
Are All Training Data Useful? A Empirical Revisit of Subset Selection in Bayesian Optimization
paper poster
Peili Mao (University of Electronic Science and Technology of China); Ke Li (University of Exeter)
Non-Gaussian Process Regression
paper poster
Yaman Kindap (University of Cambridge); Simon Godsill (University of Cambridge)
Surrogate-Assisted Evolutionary Multi-Objective Optimization for Hardware Design Space Exploration
paper poster
Renzhi Chen (National Innovative Institute of Defense Technology); Ke Li (University of Exeter)
Bayesian Spatial Clustered Regression for Count Value Data
Peng Zhao (Texas A&M University); Hou-Cheng Yang (FDA); Dipak Dey (University of Connecticut); Guanyu Hu (University of Missouri)
Efficient Variational Gaussian Processes Initialization via Kernel-based Least Squares Fitting
paper poster
Xinran Zhu (Cornell University); David Bindel (Cornell University); Jacob Gardner (University of Pennsylvania)
Variational Bayesian Inference and Learning for Continuous Switching Linear Dynamical Systems
paper poster
Jack Goffinet (Duke University); David Carlson (Duke University)
Adaptive Experimentation at Scale
paper poster
Ethan Che (Columbia University); Hongseok Namkoong (Ass Prof Columbia)
Preference-Aware Constrained Multi-Objective Bayesian Optimization
paper poster
Alaleh Ahmadianshalchi (Washington State University); Syrine Belakaria (Washington State university); Janardhan Rao Doppa (Washington State University)
Constraining Gaussian Processes to Systems of Linear Ordinary Differential Equations
paper poster
Andreas Besginow (Technische Hochschule Ostwestfalen-Lippe); Markus Lange-Hegermann (Technische Hochschule Ostwestfalen-Lippe)
Imputation and forecasting for Multi-Output Gaussian Process in Smart Grid
paper poster
JIANGJIAO XU (University of Exeter); Ke Li (University of Exeter)
Shaping of Magnetic Field Coils in Fusion Reactors using Bayesian Optimisation
paper poster
Timothy Nunn (UK Atomic Energy Authority); Vignesh Gopakumar (United Kingdom Atomic Energy Authority); Sebastien Kahn (UK Atomic Energy Authority)
Joint Point Process Model for Counterfactual Treatment–Outcome Trajectories Under Policy Interventions
paper poster
Çağlar HIZLI (Aalto University); ST John (Aalto University); Anne Juuti (University of Helsinki); Tuure Saarinen (University of Helsinki); Kirsi Pietiläinen (University of Helsinki); Pekka Marttinen (Aalto University)
PI is back! Switching Acquisition Functions in Bayesian Optimization
paper poster
Carolin Benjamins (Leibniz University Hanover); Elena Raponi (Technical University of Munich); Anja Jankovic (Sorbonne University); Koen van der Blom (Sorbonne University); Maria Laura Santoni (University of Camerino); Marius Lindauer (Leibniz University Hannover); Carola Doerr (Sorbonne University)
Actually Sparse Variational Gaussian Processes
paper poster
Harry J Cunningham (UCL); So Takao (UCL); Mark van der Wilk (Imperial College London); Marc Deisenroth (University College London)
Predicting Spatiotemporal Counts of Opioid-related Fatal Overdoses via Zero-Inflated Gaussian Processes
paper poster
Kyle Heuton (Tufts University); Shikhar Shrestha (Tufts University); Thomas Stopka (Tufts University); Jennifer Pustz (Tufts University); Liping Liu (Tufts University); Michael C Hughes (Tufts University)
Expert Selection in Distributed Gaussian Processes: A Multi-label Classification Approach
paper poster
Hamed Jalali (University of Tuebingen); Gjergji Kasneci (  University of Tuebingen)
Statistical Downscaling of Sea Surface Temperature Projections with a Multivariate Gaussian Process Model
paper poster
Ayesha Ekanayaka (University of Cincinnati); Emily Kang (University of Cincinnati); Peter Kalmus (Jet Propulsion Laboratory, California Institute of Technology); Amy Braverman (Jet Propulsion Laboratory, California Institute of Technology)
Multi-Mean Gaussian Processes: A novel probabilistic framework for multi-correlated longitudinal data
paper poster
Arthur Leroy (The University of Manchester); Mauricio A Álvarez (University of Manchester)
Spatiotemporal Residual Regularization with Kronecker Product Structure for Traffic Forecasting
Seongjin Choi (McGill University); Nicolas Saunier (Polytechnique Montreal); Martin Trepanier (École Polytechnique de Montréal); Lijun Sun (McGill University)
Uncertainty Disentanglement with Non-stationary Heteroscedastic Gaussian Processes for Active Learning
paper poster
Zeel B Patel (IIT Gandhinagar); Nipun Batra (IIT Gandhinagar); Kevin Murphy (Google)
Active Learning with Convolutional Gaussian Neural Processes for Environmental Sensor Placement
paper poster
Tom R Andersson (British Antarctic Survey); Wessel Bruinsma (Cambridge); Stratis Markou (University of Cambridge); James R Requeima (University of Cambridge); Alejandro Coca-Castro (The Alan Turing Institute); Anna Vaughan (Univeristy of Cambridge); Anna-Louise Ellis (Met Office); Matthew Lazzara (University of Wisconsin-Madison); Daniel C. Jones (British Antarctic Survey); J. Scott Hosking (British Antarctic Survey); Richard E. Turner (University of Cambridge)
Random Features Approximation for Fast Data-Driven Control
paper poster
Kimia Kazemian (Cornell University); Sarah Dean (Cornell University)
Deep Mahalanobis Gaussian Process
paper poster
Daniel A de Souza (University College London); Diego Mesquita (Getulio Vargas Foundation); César Lincoln C Mattos (Federal University of Ceará); João Paulo Gomes (Federal University of Ceará)
An Empirical Analysis of the Advantages of Finite vs.~Infinite Width Bayesian Neural Networks
paper poster
Jiayu Yao (Harvard University); Yaniv Yacoby (Harvard University); Beau Coker (Harvard University); Weiwei Pan (Harvard University); Finale Doshi-Velez (Harvard)
Non-exchangeability in Infinite Switching Linear Dynamical Systems
Victor Geadah (Princeton University); Jonathan W Pillow (Princeton University)
Posterior Consistency for Gaussian Process Surrogate Models with Generalized Observations
paper poster
Rujian Chen (MIT); John Fisher (MIT)
Recommendations for Baselines and Benchmarking Approximate Gaussian Processes
paper poster
Sebastian W Ober (University of Cambridge); David R Burt (Massachusetts Institute of Technology); Artem Artemev (Imperial College London); Mark van der Wilk (Imperial College London)
Challenges in Gaussian Processes for Non Intrusive Load Monitoring
Aadesh K Desai (IIT Gandhinagar); Gautam Prashant Vashishtha (IIT Gandhinagar); Zeel B Patel (IIT Gandhinagar); Nipun Batra (IIT Gandhinagar)