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05/29/2023
Cross-Entropy Estimators for Sequential Experiment Design with Reinforcement Learning
Reinforcement learning can effectively learn amortised design policies f...
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05/25/2023
Learning Directed Graphical Models with Optimal Transport
Estimating the parameters of a probabilistic directed graphical model fr...
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02/20/2023
Transformed Distribution Matching for Missing Value Imputation
We study the problem of imputing missing values in a dataset, which has ...
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09/27/2022
Learning to Counter: Stochastic Feature-based Learning for Diverse Counterfactual Explanations
Interpretable machine learning seeks to understand the reasoning process...
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02/02/2022
Optimizing Sequential Experimental Design with Deep Reinforcement Learning
Bayesian approaches developed to solve the optimal design of sequential ...
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03/06/2020
Rethinking Sparse Gaussian Processes: Bayesian Approaches to Inducing-Variable Approximations
Variational inference techniques based on inducing variables provide an ...
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05/24/2018
Log Gaussian Cox Process Networks
We generalize the log Gaussian Cox process (LGCP) framework to model mul...
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06/18/2012