Description: Simulation-based Inference is the next evolution in statistics
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 cyberinfrastr
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 wi
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.