DecisionProgramming.jl is a Julia package for solving multi-stage decision problems under uncertainty, modeled using influence diagrams. Internally, it relies on mathematical optimization. Decision models can be embedded within other optimization models.
This article explores the Cell Lists algorithm for performing a fixed-radius near neighbors search through practical implementation in Julia language, analyzes the algorithm theoretically, and benchmarks its performance compared to brute force.
This article explores the definition and properties of Conditional Value at Risk, a coherent risk measure for measuring tail risk. We also provide an implementation in Julia language for discrete probability distributions.
Read on to learn essential software engineering principles, practices, and tools, and how scientists can write code into collaborative software packages.
This article discusses how to use Julia language and Atom editor for mathematical programming workflow.