Alert button
Picture for Christopher Frye

Christopher Frye

Alert button

Task-specific experimental design for treatment effect estimation

Jun 08, 2023
Bethany Connolly, Kim Moore, Tobias Schwedes, Alexander Adam, Gary Willis, Ilya Feige, Christopher Frye

Figure 1 for Task-specific experimental design for treatment effect estimation
Figure 2 for Task-specific experimental design for treatment effect estimation
Figure 3 for Task-specific experimental design for treatment effect estimation
Figure 4 for Task-specific experimental design for treatment effect estimation
Viaarxiv icon

Learning to Noise: Application-Agnostic Data Sharing with Local Differential Privacy

Oct 23, 2020
Alex Mansbridge, Gregory Barbour, Davide Piras, Christopher Frye, Ilya Feige, David Barber

Figure 1 for Learning to Noise: Application-Agnostic Data Sharing with Local Differential Privacy
Figure 2 for Learning to Noise: Application-Agnostic Data Sharing with Local Differential Privacy
Figure 3 for Learning to Noise: Application-Agnostic Data Sharing with Local Differential Privacy
Figure 4 for Learning to Noise: Application-Agnostic Data Sharing with Local Differential Privacy
Viaarxiv icon

Explainability for fair machine learning

Oct 14, 2020
Tom Begley, Tobias Schwedes, Christopher Frye, Ilya Feige

Figure 1 for Explainability for fair machine learning
Figure 2 for Explainability for fair machine learning
Figure 3 for Explainability for fair machine learning
Figure 4 for Explainability for fair machine learning
Viaarxiv icon

Human-interpretable model explainability on high-dimensional data

Oct 14, 2020
Damien de Mijolla, Christopher Frye, Markus Kunesch, John Mansir, Ilya Feige

Figure 1 for Human-interpretable model explainability on high-dimensional data
Figure 2 for Human-interpretable model explainability on high-dimensional data
Figure 3 for Human-interpretable model explainability on high-dimensional data
Figure 4 for Human-interpretable model explainability on high-dimensional data
Viaarxiv icon

Shapley-based explainability on the data manifold

Jun 01, 2020
Christopher Frye, Damien de Mijolla, Laurence Cowton, Megan Stanley, Ilya Feige

Figure 1 for Shapley-based explainability on the data manifold
Figure 2 for Shapley-based explainability on the data manifold
Figure 3 for Shapley-based explainability on the data manifold
Figure 4 for Shapley-based explainability on the data manifold
Viaarxiv icon

Asymmetric Shapley values: incorporating causal knowledge into model-agnostic explainability

Oct 14, 2019
Christopher Frye, Ilya Feige, Colin Rowat

Figure 1 for Asymmetric Shapley values: incorporating causal knowledge into model-agnostic explainability
Figure 2 for Asymmetric Shapley values: incorporating causal knowledge into model-agnostic explainability
Figure 3 for Asymmetric Shapley values: incorporating causal knowledge into model-agnostic explainability
Figure 4 for Asymmetric Shapley values: incorporating causal knowledge into model-agnostic explainability
Viaarxiv icon

Parenting: Safe Reinforcement Learning from Human Input

Feb 18, 2019
Christopher Frye, Ilya Feige

Figure 1 for Parenting: Safe Reinforcement Learning from Human Input
Figure 2 for Parenting: Safe Reinforcement Learning from Human Input
Figure 3 for Parenting: Safe Reinforcement Learning from Human Input
Figure 4 for Parenting: Safe Reinforcement Learning from Human Input
Viaarxiv icon

JUNIPR: a Framework for Unsupervised Machine Learning in Particle Physics

Apr 25, 2018
Anders Andreassen, Ilya Feige, Christopher Frye, Matthew D. Schwartz

Figure 1 for JUNIPR: a Framework for Unsupervised Machine Learning in Particle Physics
Figure 2 for JUNIPR: a Framework for Unsupervised Machine Learning in Particle Physics
Figure 3 for JUNIPR: a Framework for Unsupervised Machine Learning in Particle Physics
Figure 4 for JUNIPR: a Framework for Unsupervised Machine Learning in Particle Physics
Viaarxiv icon