Deterministic and Probabilistic Simulation Workflows

Coming soon. (Julia Hub)

Overview

Target Users:

Julia Hub’s deterministic and probabilistic simulation workflows with SciML (including Modeling Toolkit) can be used by modelers or researchers who are either bringing their own model or using one readily available, and are interested in using it to ask various questions relevant for supporting decisionmakers. Users may be working under time constraints and more focused on deterministic answers to their questions, preferring to work with simulation tools with high performance and shorter execution times. Especially when working with larger and more complex models, users may want to rely on tools that give them a performance advantage, and can figure out or suggest optimal simulation options on the backend.

Features Supported:

Users can use SciML and MTK do simulation workflows to support policy-relevant questions:

Deterministic and probabilistic calibration
Deterministic and probabilistic simulation (including forecasts)
Implementing interventions
Risk based optimization of intervention policies, under uncertainty
Generate ensemble forecasts

Installation and Configuration Instructions

(please include links to repositories)

https://sciml.ai/

https://github.com/SciML/ModelingToolkit.jl

Examples

(please include visuals, screenshots of inputs and outputs, etc.)