Optimizing Stochastic and Multiple Fitness Functions. - Joseph L. Breeden (Evolutionary Programming, 1995)

GA-Optimal Fitness Functions. - Joseph L. Breeden (Evolutionary Programming, 1998)

Modeling data with multiple time dimensions. - Joseph L. Breeden (Comput. Stat. Data Anal., 2007)

Monte Carlo scenario generation for retail loan portfolios. - Joseph L. Breeden; D. Ingram (J. Oper. Res. Soc., 2010)

Incorporating lifecycle and environment in loan-level forecasts and stress tests. - Joseph L. Breeden (Eur. J. Oper. Res., 2016)

Solutions to specification errors in stress testing models. - Joseph L. Breeden; Lyn Thomas (J. Oper. Res. Soc., 2016)

Multihorizon discrete time survival models. - Joseph L. Breeden; Jonathan Crook (J. Oper. Res. Soc., 2022)

Stabilizing machine learning models with Age-Period-Cohort inputs for scoring and stress testing. - Joseph L. Breeden; Yevgeniya Leonova (Frontiers Appl. Math. Stat., 2023)

Classical and quantum computing methods for estimating loan-level risk distributions. - Joseph L. Breeden; Yevgeniya Leonova (J. Oper. Res. Soc., 2023)

Scoring AI-generated policy recommendations with Risk-Adjusted Gain in Net Present Happiness. - Joseph L. Breeden (AI Ethics, 2024)

Metamorphic Testing and exploration for Machine Learning credit score models. - Zhihao Ying; Anthony Graham Bellotti; Joseph L. Breeden; Dave Towey (Inf. Softw. Technol., 2025)

The evolution of goals in AI agents. - Joseph L. Breeden (AI Ethics, 2025)