Neill D. F. Campbell

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University of Bath

Black-box density function estimation using recursive partitioning

We present a novel approach to Bayesian inference and general Bayesian c...
10/26/2020 ∙ by Erik Bodin, et al. ∙ 0 ∙ share

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DiverseNet: When One Right Answer is not Enough

Many structured prediction tasks in machine vision have a collection of ...
08/24/2020 ∙ by Michael Firman, et al. ∙ 32 ∙ share

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Compositional uncertainty in deep Gaussian processes

Gaussian processes (GPs) are nonparametric priors over functions, and fi...
09/17/2019 ∙ by Ivan Ustyuzhaninov, et al. ∙ 13 ∙ share

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Modulated Bayesian Optimization using Latent Gaussian Process Models

We present an approach to Bayesian Optimization that allows for robust s...
06/26/2019 ∙ by Erik Bodin, et al. ∙ 2 ∙ share

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Monotonic Gaussian Process Flow

We propose a new framework of imposing monotonicity constraints in a Bay...
05/30/2019 ∙ by Ivan Ustyuzhaninov, et al. ∙ 0 ∙ share

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Gaussian Process Deep Belief Networks: A Smooth Generative Model of Shape with Uncertainty Propagation

The shape of an object is an important characteristic for many vision pr...
12/13/2018 ∙ by Alessandro Di Martino, et al. ∙ 14 ∙ share

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The GAN that Warped: Semantic Attribute Editing with Unpaired Data

Deep neural networks have recently been used to edit images with great s...
11/30/2018 ∙ by Garoe Dorta, et al. ∙ 12 ∙ share

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Sequence Alignment with Dirichlet Process Mixtures

We present a probabilistic model for unsupervised alignment of high-dime...
11/26/2018 ∙ by Ieva Kazlauskaite, et al. ∙ 0 ∙ share

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DP-GP-LVM: A Bayesian Non-Parametric Model for Learning Multivariate Dependency Structures

We present a non-parametric Bayesian latent variable model capable of le...
07/12/2018 ∙ by Andrew R. Lawrence, et al. ∙ 8 ∙ share

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Training VAEs Under Structured Residuals

Variational auto-encoders (VAEs) are a popular and powerful deep generat...
04/03/2018 ∙ by Garoe Dorta, et al. ∙ 0 ∙ share

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Gaussian Process Latent Variable Alignment Learning

We present a model that can automatically learn alignments between high-...
03/07/2018 ∙ by Ieva Kazlauskaite, et al. ∙ 0 ∙ share

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Structured Uncertainty Prediction Networks

This paper is the first work to propose a network to predict a structure...
02/20/2018 ∙ by Garoe Dorta, et al. ∙ 0 ∙ share

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Nonparametric Inference for Auto-Encoding Variational Bayes

We would like to learn latent representations that are low-dimensional a...
12/18/2017 ∙ by Erik Bodin, et al. ∙ 0 ∙ share

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Latent Gaussian Process Regression

We introduce Latent Gaussian Process Regression which is a latent variab...
07/18/2017 ∙ by Erik Bodin, et al. ∙ 0 ∙ share

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Responsive Action-based Video Synthesis

We propose technology to enable a new medium of expression, where video ...
05/20/2017 ∙ by Corneliu Ilisescu, et al. ∙ 0 ∙ share

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Hierarchical Subquery Evaluation for Active Learning on a Graph

To train good supervised and semi-supervised object classifiers, it is c...
04/30/2015 ∙ by Oisin Mac Aodha, et al. ∙ 0 ∙ share

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Neill D. F. Campbell

Featured Co-authors

Jan Kautz

Carl Henrik Ek

Zhenwen Dai

Gabriel J. Brostow

Lourdes Agapito

Oisin Mac Aodha

Ivan Ustyuzhaninov

Erik Bodin

Ieva Kazlauskaite

Markus Kaiser

Michael Firman

Black-box density function estimation using recursive partitioning

DiverseNet: When One Right Answer is not Enough

Compositional uncertainty in deep Gaussian processes

Modulated Bayesian Optimization using Latent Gaussian Process Models

Monotonic Gaussian Process Flow

Gaussian Process Deep Belief Networks: A Smooth Generative Model of Shape with Uncertainty Propagation

The GAN that Warped: Semantic Attribute Editing with Unpaired Data

Sequence Alignment with Dirichlet Process Mixtures

DP-GP-LVM: A Bayesian Non-Parametric Model for Learning Multivariate Dependency Structures

Training VAEs Under Structured Residuals

Gaussian Process Latent Variable Alignment Learning

Structured Uncertainty Prediction Networks

Nonparametric Inference for Auto-Encoding Variational Bayes

Latent Gaussian Process Regression

Responsive Action-based Video Synthesis

Hierarchical Subquery Evaluation for Active Learning on a Graph