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This website under construction.

Introduction

Simulators are the modern manifestation of scientific theories. They implement mechanistic models of the underlying natural phenomena of interest as well as models for the instruments used to observe those phenomena. The expressiveness of programming languages facilitates the development of complex, high-fidelity simulations and the power of modern computing provides the ability to generate synthetic data from them. The flexibility of simulators has made them critical research tools (and major cyberinfrastructure investments) for predicting how systems will behave across many areas of science and engineering. Unfortunately, despite their predictive power, these simulators are poorly suited for statistical inference, which is a core aspect of data-intensive science. To meet this challenge, there are an emerging set of techniques for simulation-based inference (SBI).

Simulation-based inference is the next step in the methodological evolution of statistical practice in the sciences. SBI provides qualitatively new capabilities that can transform scientific practice in fields as diverse as evolutionary biology, systems biology, neuroscience, gravitational wave astronomy, dark matter astrophysics, cosmology, and particle physics. Inference problems in these areas are challenging because they involve high-dimensional, richly-structured spaces. Empowering domain scientists with the ability to directly infer from data the properties of the underlying mechanistic models that they are developing would be transformative.

SBI has also proven to be an effective lingua franca that facilitates communication between domain scientists and methodological experts, supports convergence research, and accelerates cross-pollination of ideas between fields.

Selected Papers

The plan is to turn this page into a crowd-sourced community resource that can collect recent papers including methodological developments and applications. Here are some links to get started:

Reviews

Applications

Selected Software

An initial list of SBI-related software packages

About this site

This page is maintained by Kyle Cranmer and hosted via GitHub pages via the simulation-based-inference GitHub organization. As mentioned above, the plan is to turn this page into a crowd-sourced community resource that can collect recent papers including methodological developments and applications. We are working on the underlying infrastructure, but it will probably be similar to what drives the IRIS-HEP webpages (source) and/or something like this living review.