On Contrastive Learning for Likelihood-free Inference

Likelihood-free methods perform parameter inference in stochastic simulator models where evaluating the likelihood is intractable but sampling synthetic data is possible. One class of methods for this likelihood-free problem uses a classifier to distinguish between pairs of parameter-observation samples generated using the simulator and pairs sampled from some reference distribution, which implicitly learns a density ratio proportional to the likelihood. Another popular class of methods fits a conditional distribution to the parameter posterior directly, and a particular recent variant allows for the use of flexible neural density estimators for this task. In this work, we show that both of these approaches can be unified under a general contrastive learning scheme, and clarify how they should be run and compared.Comment: Appeared at ICML 202

Neural Spline Flows

A normalizing flow models a complex probability density as an invertible transformation of a simple base density. Flows based on either coupling or autoregressive transforms both offer exact density evaluation and sampling, but rely on the parameterization of an easily invertible elementwise transformation, whose choice determines the flexibility of these models. Building upon recent work, we propose a fully-differentiable module based on monotonic rational-quadratic splines, which enhances the flexibility of both coupling and autoregressive transforms while retaining analytic invertibility. We demonstrate that neural spline flows improve density estimation, variational inference, and generative modeling of images.Comment: Published at the 33rd Conference on Neural Information Processing Systems (NeurIPS 2019), Vancouver, Canad

The experiences of men in prison who do not receive visits from family or friends: A qualitative systematic review

Background. Visits present an opportunity for prisoners to preserve family ties and reduce isolation, but not all receive visits from family or friends whilst incarcerated.Aims. To locate, appraise and synthesise qualitative data on the experiences of adult male prisoners (aged 18 years+) who do not receive prison visits from family or friends.Methods. Nine electronic databases were searched from the date of their inception until March 2023. The quality of included studies was assessed using the Critical Appraisal Skills Programme (CASP) checklist for qualitative studies, and data from the studies were synthesised using the thematic synthesis method.Results. Eighteen studies from seven countries (the USA, the UK [England, Northern Ireland & Scotland], Canada, Netherlands and the Philippines were eligible for inclusion. Three main themes emerged: (1) reasons for not receiving visits; (2) harmful effects of not receiving visits; (3) the value of volunteer visitor programmes. Practical problems were cited as interfering with visiting opportunities, but also some prisoners or families chose not to meet in prison.Loneliness and depression were extensively described as effects of not receiving visits. Qualities associated with volunteer visitors included raised self-esteem, improved mood and personal growth.Conclusions. Narratives of the experiences of adult men in prison without visits from family or friends suggest that not only the practical difficulties of imprisonment affect visiting; barriers that prisoners themselves impose would merit further exploration, as would family and relationship dynamics during incarceration and the emotional impact of prison visits, for both prisoners and their families. There are suggestions of therapeutic as well as humanitarianbenefits from volunteer visiting programmes. There is a gap in the literature about any specific effect on rebuilding family relationships