Safe-Level-SMOTE: Safe-Level-Synthetic Minority Over-Sampling TEchnique for Handling the Class Imbalanced Problem. - Chumphol Bunkhumpornpat; Krung Sinapiromsaran; Chidchanok Lursinsap (PAKDD, 2009)

MUTE: Majority under-sampling technique. - Chumphol Bunkhumpornpat; Krung Sinapiromsaran; Chidchanok Lursinsap (ICICS, 2011)

DBSMOTE: Density-Based Synthetic Minority Over-sampling TEchnique. - Chumphol Bunkhumpornpat; Krung Sinapiromsaran; Chidchanok Lursinsap (Appl. Intell., 2012)

Parameter-Free Imputation for Imbalance Datasets. - Jintana Takum; Chumphol Bunkhumpornpat (ICADL, 2014)

CORE: core-based synthetic minority over-sampling and borderline majority under-sampling technique. - Chumphol Bunkhumpornpat; Krung Sinapiromsaran (Int. J. Data Min. Bioinform., 2015)

DBMUTE: density-based majority under-sampling technique. - Chumphol Bunkhumpornpat; Krung Sinapiromsaran (Knowl. Inf. Syst., 2017)

FLEX-SMOTE: Synthetic over-sampling technique that flexibly adjusts to different minority class distributions. - Chumphol Bunkhumpornpat; Ekkarat Boonchieng; Varin Chouvatut; David Lipsky (Patterns, 2024)