The primary foundational paper for this concept is , which provides a comprehensive review of the framework. Key Scientific Papers on Sloppiness
Below are several major papers and resources that define the field: sloppy
: Researchers use the FIM to measure how distinguishable models are based on their predictions. In sloppy models, FIM eigenvalues are distributed roughly evenly over many decades. The primary foundational paper for this concept is
: A few parameter combinations ("stiff") tightly constrain model behavior, while others ("sloppy") can vary by orders of magnitude without changing the output. : A few parameter combinations ("stiff") tightly constrain
: The set of all possible model predictions forms a "manifold" that is often extremely narrow in some dimensions, resembling a "hyper-ribbon". Other Contexts of "Sloppy" in Research
(Machta et al., 2013): Explains why complicated microscopic processes often result in simple macroscopic behavior. Core Concepts of "Sloppy" Research