On Riemannian Latent Variable Models and Pullback Metrics

Noémie Jaquier · KTH Royal Institute of Technology

Computation-Aware Kalman Filtering and Smoothing

Marvin Pförtner · University of Tübingen

On Modernising Sparse Gaussian Processes

Yingzhen Li · Imperial College London

Unexpected Improvements to Expected Improvement for Bayesian Optimization

Sebastian Ament · Meta

Exploring phenotypes and genotypes with a robot scientist

Paul Jensen · University of Michigan

Cost-aware Bayesian Optimization via the Pandora's Box Gittins Index

Qian Xie · Cornell University

Accurate predictions on small data (and time series) with the tabular foundation model TabPFN

Frank Hutter · University of Freiburg

Text-to-Text Regression

Xingyou (Richard) Song · Google DeepMind

Black-box Optimization for Humans with Unknown Preferences

Peter I. Frazier · Cornell University

Uncertain Surface Reconstruction

Silvia Sellán · University of Toronto

ML-guided nanobody design targeting COVID-19

Zelda Mariet · Google Brain

Multi-fidelity Scientific Discovery and Design

Diana Cai · Princeton University

Gaussian processes at the Helm(holtz)

David R. Burt · MIT

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

Ben Adlam · Google Brain

Satellite imagery, machine learning, and geospatial modeling: Challenges and opportunities

Esther Rolf · Harvard University

Scalable Deep Bayesian optimization over Structured Inputs

Jacob R. Gardner · University of Pennsylvania

Building neural networks that know what they don’t know

Balaji Lakshminarayanan · Google Brain

Bayesian Optimisation for Neural Architecture Search

Binxin (Robin) Ru · University of Oxford

Automated augmented conjugate inference for Gaussian processes and a Julia perspective on Gaussian Processes

Théo Galy-Fajou · Technische Universität Berlin

Dual Parameterization of Sparse Variational Gaussian Processes

Vincent Adam · University Pompeu Fabra

Structured Inter-domain Inducing Points for Variational Gaussian Processes

Shengyang Sun · University of Toronto

Spatial and spatio-temporal models in the time of COVID-19

Marta Blangiardo · Imperial College London

Spherical Gaussian Processes

James Hensman · Amazon

Fast Discovery of Pairwise Interactions in High Dimensions using Gaussian Processes

Tamara Broderick · MIT