Tuesday, 24th January 2023 An overview of recent mutual information estimators Abstract: Mutual information is a useful and principled measure for quantifying the relationship between random variables. As such, mutual information is applied in many disciplines, including neuroscience where it is used to explore coding in neural populations. However, estimating mutual information can be challenging, especially if the random variables of interest are high-dimensional. In recent years, many new estimators have been proposed, benefiting from advances in machine learning. In this talk, I will provide an overview of recent mutual information estimators, comparing and contrasting some of the approaches. Event type: Workshop Date: Tuesday, 24th January 2023 Time: 11:00 Location: G.07 - note change in location Speaker(s): Arno Onken Chair/Host: Ian Simpson This article was published on 2024-11-22
