Michael Thomas Smith | DeepAI

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∙ 05/04/2022

Modelling calibration uncertainty in networks of environmental sensors

Networks of low-cost sensors are becoming ubiquitous, but often suffer f...

1 Michael Thomas Smith, et al. ∙

∙ 09/19/2019

Adversarial Vulnerability Bounds for Gaussian Process Classification

Machine learning (ML) classification is increasingly used in safety-crit...

6 Michael Thomas Smith, et al. ∙

∙ 09/19/2019

Differentially Private Regression and Classification with Sparse Gaussian Processes

A continuing challenge for machine learning is providing methods to perf...

12 Michael Thomas Smith, et al. ∙

∙ 06/22/2019

Multi-task Learning for Aggregated Data using Gaussian Processes

Aggregated data is commonplace in areas such as epidemiology and demogra...

4 Fariba Yousefi, et al. ∙

∙ 09/06/2018

Gaussian Process Regression for Binned Data

Many datasets are in the form of tables of binned data. Performing regre...

0 Michael Thomas Smith, et al. ∙

∙ 11/17/2017

How Wrong Am I? - Studying Adversarial Examples and their Impact on Uncertainty in Gaussian Process Machine Learning Models

Machine learning models are vulnerable to adversarial examples: minor, i...

0 Kathrin Grosse, et al. ∙

∙ 06/02/2016

Differentially Private Gaussian Processes

A major challenge for machine learning is increasing the availability of...

0 Michael Thomas Smith, et al. ∙

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