Articles by Geoff Pleiss

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Variational Nearest Neighbor Gaussian Process

21 November 2024 by Luhuan Wu and others at

Columbia University

Machine Learning

Computation-Aware Gaussian Processes: Model Selection And Linear-Time Inference

1 November 2024 by Jonathan Wenger and others

Machine Learning

Theoretical Limitations of Ensembles in the Age of Overparameterization

21 October 2024 by Niclas Dern and others

Machine Learning

How Useful is Intermittent, Asynchronous Expert Feedback for Bayesian Optimization?

10 June 2024 by Agustinus Kristiadi and others

Machine Learning

Online Continual Learning of Video Diffusion Models From a Single Video Stream

7 June 2024 by Jason Yoo and others

Computer Vision and Pattern Recognition, Machine Learning

Layerwise Proximal Replay: A Proximal Point Method for Online Continual Learning

7 June 2024 by Jason Yoo and others

Machine Learning

How Inductive Bias in Machine Learning Aligns with Optimality in Economic Dynamics

7 June 2024 by Mahdi Ebrahimi Kahou and others at

University of British Columbia

General Economics, Economics

Approximation-Aware Bayesian Optimization

6 June 2024 by Natalie Maus and others at

Columbia University

Machine Learning

Large-Scale Gaussian Processes via Alternating Projection

8 March 2024 by Kaiwen Wu and others at

Columbia University

Machine Learning

MCMC-driven learning

14 February 2024 by Alexandre Bouchard-Côté and others

Machine Learning, Statistics Theory

A Sober Look at LLMs for Material Discovery: Are They Actually Good for Bayesian Optimization Over Molecules?

7 February 2024 by Agustinus Kristiadi and others at

University of British Columbia

Machine Learning

Pathologies of Predictive Diversity in Deep Ensembles

9 January 2024 by Taiga Abe and others

Machine Learning

CoLA: Exploiting Compositional Structure for Automatic and Efficient Numerical Linear Algebra

29 November 2023 by Andres Potapczynski and others

Machine Learning, Numerical Analysis

Sharp Calibrated Gaussian Processes

16 November 2023 by Alexandre Capone and others

Machine Learning

Posterior and Computational Uncertainty in Gaussian Processes

9 October 2023 by Jonathan Wenger and others

Machine Learning, Numerical Analysis

Deep Ensembles Work, But Are They Necessary?

13 October 2022 by Taiga Abe and others

Machine Learning

Scalable Cross Validation Losses for Gaussian Process Models

9 March 2022 by Martin Jankowiak and Geoff Pleiss

Machine Learning

Preconditioning for Scalable Gaussian Process Hyperparameter Optimization

28 January 2022 by Jonathan Wenger and others

Machine Learning, Numerical Analysis

The Limitations of Large Width in Neural Networks: A Deep Gaussian Process Perspective

8 November 2021 by Geoff Pleiss and John Cunningham

Machine Learning

Rectangular Flows for Manifold Learning

29 October 2021 by Anthony Caterini and others

Machine Learning

Bias-Free Scalable Gaussian Processes via Randomized Truncations

29 June 2021 by Andres Potapczynski and others

Machine Learning

Hierarchical Inducing Point Gaussian Process for Inter-domain Observations

24 June 2021 by Luhuan Wu and others

Machine Learning

Deep Sigma Point Processes

26 December 2020 by Martin Jankowiak and others

Machine Learning

Fast Matrix Square Roots with Applications to Gaussian Processes and Bayesian Optimization

30 November 2020 by Geoff Pleiss and others

Machine Learning

Uses and Abuses of the Cross-Entropy Loss: Case Studies in Modern Deep Learning

10 November 2020 by Elliott Gordon-Rodriguez and others

Machine Learning

Harnessing Interpretable and Unsupervised Machine Learning to Address Big Data from Modern X-ray Diffraction

10 August 2020 by Jordan Venderley and others

Parametric Gaussian Process Regressors

15 February 2020 by Martin Jankowiak and others

Machine Learning

Identifying Mislabeled Data using the Area Under the Margin Ranking

29 January 2020 by Geoff Pleiss and others

Machine Learning, Computer Vision and Pattern Recognition

Convolutional Networks with Dense Connectivity

8 January 2020 by Gao Huang and others

Machine Learning, Computer Vision and Pattern Recognition

Exact Gaussian Processes on a Million Data Points

10 December 2019 by Ke Alexander Wang and others

Machine Learning, Distributed, Parallel, and Cluster Computing

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Machine Learning Computer Vision and Pattern Recognition Numerical Analysis General Economics Economics Statistics Theory Computation Strongly Correlated Electrons Disordered Systems and Neural Networks Distributed, Parallel, and Cluster Computing Computers and Society