36 citations · 60 across the 5 of their papers we have counts for
3 papers · 1 filter
Antifragility Predicts the Robustness and Evolvability of Biological Networks through Multi-class Classification with a Convolutional Neural Network
Hyobin Kim, Stalin Muñoz, Pamela Osuna +1
Robustness and evolvability are essential properties to the evolution of biological networks. To determine if a biological network is robust and/or evolvable, it is required to com…
A Multilayer Structure Facilitates the Production of Antifragile Systems in Boolean Network Models
Hyobin Kim, Omar K. Pineda, Carlos Gershenson
Antifragility is a property from which systems are able to resist stress and furthermore benefit from it. Even though antifragile dynamics is found in various real-world complex sy…
A Novel Antifragility Measure Based on Satisfaction and Its Application to Random and Biological Boolean Networks
Omar K. Pineda, Hyobin Kim, Carlos Gershenson
Antifragility is a property that enhances the capability of a system in response to external perturbations. Although the concept has been applied in many areas, a practical measure…