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Jeffrey Spence

2 accepted papers

2020

Flexible mean field variational inference using mixtures of non-overlapping exponential families

NeurIPS 2020spotlight

Sparse models are desirable for many applications across diverse domains as they can perform automatic variable selection, aid interpretability, and provide regularization. When fitting sparse models in a Bayesian framework, however, analytically obtaining a posterior distribution over the paramete…

2018

A Likelihood-Free Inference Framework for Population Genetic Data using Exchangeable Neural Networks

NeurIPS 2018spotlight

An explosion of high-throughput DNA sequencing in the past decade has led to a surge of interest in population-scale inference with whole-genome data. Recent work in population genetics has centered on designing inference methods for relatively simple model classes, and few scalable general-purpose…