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08/20/2023
SE(3) Equivariant Augmented Coupling Flows
Coupling normalizing flows allow for fast sampling and density evaluatio...
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07/12/2023
Online Laplace Model Selection Revisited
The Laplace approximation provides a closed-form model selection objecti...
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06/20/2023
Sampling from Gaussian Process Posteriors using Stochastic Gradient Descent
Gaussian processes are a powerful framework for quantifying uncertainty ...
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02/20/2023
Fast and Painless Image Reconstruction in Deep Image Prior Subspaces
The deep image prior (DIP) is a state-of-the-art unsupervised approach f...
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10/10/2022
Sampling-based inference for large linear models, with application to linearised Laplace
Large-scale linear models are ubiquitous throughout machine learning, wi...
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07/11/2022
Bayesian Experimental Design for Computed Tomography with the Linearised Deep Image Prior
We investigate adaptive design based on a single sparse pilot scan for g...
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06/17/2022
Adapting the Linearised Laplace Model Evidence for Modern Deep Learning
The linearised Laplace method for estimating model uncertainty has recei...
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02/28/2022
A Probabilistic Deep Image Prior for Computational Tomography
Existing deep-learning based tomographic image reconstruction methods do...
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12/13/2021
Addressing Bias in Active Learning with Depth Uncertainty Networks... or Not
Farquhar et al. [2021] show that correcting for active learning bias wit...
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12/13/2021
Depth Uncertainty Networks for Active Learning
In active learning, the size and complexity of the training dataset chan...
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11/15/2020
Uncertainty as a Form of Transparency: Measuring, Communicating, and Using Uncertainty
Transparency of algorithmic systems entails exposing system properties t...
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10/28/2020
Expressive yet Tractable Bayesian Deep Learning via Subnetwork Inference
The Bayesian paradigm has the potential to solve some of the core issues...
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06/15/2020
Depth Uncertainty in Neural Networks
Existing methods for estimating uncertainty in deep learning tend to req...
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06/11/2020
Getting a CLUE: A Method for Explaining Uncertainty Estimates
Both uncertainty estimation and interpretability are important factors f...
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02/06/2020
Variational Depth Search in ResNets
One-shot neural architecture search allows joint learning of weights and...
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01/27/2019
