Center for Cosmology and Particle Physics, New York University, New York, NY 10003;
Center for Data Science, New York University, New York, NY 10011.
Proc Natl Acad Sci U S A. 2020 Dec 1;117(48):30055-30062. doi: 10.1073/pnas.1912789117. Epub 2020 May 29.
Many domains of science have developed complex simulations to describe phenomena of interest. While these simulations provide high-fidelity models, they are poorly suited for inference and lead to challenging inverse problems. We review the rapidly developing field of simulation-based inference and identify the forces giving additional momentum to the field. Finally, we describe how the frontier is expanding so that a broad audience can appreciate the profound influence these developments may have on science.
许多科学领域都开发了复杂的模拟来描述感兴趣的现象。虽然这些模拟提供了高保真模型，但它们不适合进行推理，并且导致了具有挑战性的反问题。我们回顾了基于模拟的推理这一快速发展的领域，并确定了为该领域提供额外动力的力量。最后，我们描述了前沿领域如何扩展，以便更广泛的受众可以欣赏这些发展可能对科学产生的深远影响。
