83 citations · 225 across the 27 of their papers we have counts for
28 papers
Statistically Efficient Bayesian Sequential Experiment Design via Reinforcement Learning with Cross-Entropy Estimators
Tom Blau, Iadine Chades, Amir Dezfouli +2
Reinforcement learning can learn amortised design policies for designing sequences of experiments. However, current amortised methods rely on estimators of expected information gai…
Parameter Estimation in DAGs from Incomplete Data via Optimal Transport
Vy Vo, Trung Le, Tung-Long Vuong +3
Estimating the parameters of a probabilistic directed graphical model from incomplete data is a long-standing challenge. This is because, in the presence of latent variables, both…
Transformed Distribution Matching for Missing Value Imputation
He Zhao, Ke Sun, Amir Dezfouli +1
We study the problem of imputing missing values in a dataset, which has important applications in many domains. The key to missing value imputation is to capture the data distribut…
Free-Form Variational Inference for Gaussian Process State-Space Models
Xuhui Fan, Edwin V. Bonilla, Terence J. O'Kane +1
Gaussian process state-space models (GPSSMs) provide a principled and flexible approach to modeling the dynamics of a latent state, which is observed at discrete-time points via a…
Recurrent Neural Networks and Universal Approximation of Bayesian Filters
Adrian N. Bishop, Edwin V. Bonilla
We consider the Bayesian optimal filtering problem: i.e. estimating some conditional statistics of a latent time-series signal from an observation sequence. Classical approaches of…
Feature-based Learning for Diverse and Privacy-Preserving Counterfactual Explanations
Vy Vo, Trung Le, Van Nguyen +4
Interpretable machine learning seeks to understand the reasoning process of complex black-box systems that are long notorious for lack of explainability. One flourishing approach i…