My research is in machine learning for science, with a focus on developing methods for (Bayesian) inference and design.
- eLife: Designing Optimal Behavioral Experiments Using Machine Learning
- TMLR: Conditional Sampling of Variational Autoencoders via Iterated Approximate Ancestral Sampling
- ICML: Is Learning Summary Statistics Necessary for Likelihood-free Inference?
- TMLR: Estimating the Density Ratio between Distributions with High Discrepancy using Multinomial Logistic Regression
- TMLR: Bayesian Optimization with Informative Covariance