FaSS: Ensembles for Stable Learners. - Kai Ming Ting; Jonathan R. Wells; Swee Chuan Tan; Shyh Wei Teng; Geoffrey I. Webb (MCS, 2009)

Multi-dimensional Mass Estimation and Mass-based Clustering. - Kai Ming Ting; Jonathan R. Wells (ICDM, 2010)

Density Estimation Based on Mass. - Kai Ming Ting; Takashi Washio; Jonathan R. Wells; Fei Tony Liu (ICDM, 2011)

Feature-subspace aggregating: ensembles for stable and unstable learners. - Kai Ming Ting; Jonathan R. Wells; Swee Chuan Tan; Shyh Wei Teng; Geoffrey I. Webb (Mach. Learn., 2011)

A non-time series approach to vehicle related time series problems. - Jonathan R. Wells; Kai Ming Ting; Naiwala P. Chandrasiri (AusDM, 2012)

Local Models - the Key to Boosting Stable Learners Successfully. - Kai Ming Ting; Lian Zhu; Jonathan R. Wells (Comput. Intell., 2013)

DEMass: a new density estimator for big data. - Kai Ming Ting; Takashi Washio; Jonathan R. Wells; Fei Tony Liu; Sunil Aryal (Knowl. Inf. Syst., 2013)

Efficient Anomaly Detection by Isolation Using Nearest Neighbour Ensemble. - Tharindu R. Bandaragoda; Kai Ming Ting; David W. Albrecht; Fei Tony Liu; Jonathan R. Wells (ICDM Workshops, 2014)

Improving iForest with Relative Mass. - Sunil Aryal; Kai Ming Ting; Jonathan R. Wells; Takashi Washio (PAKDD (2), 2014)

LiNearN: A new approach to nearest neighbour density estimator. - Jonathan R. Wells; Kai Ming Ting; Takashi Washio (Pattern Recognit., 2014)

A simple efficient density estimator that enables fast systematic search. - Jonathan R. Wells; Kai Ming Ting (CoRR, 2017)

Defying the gravity of learning curve: a characteristic of nearest neighbour anomaly detectors. - Kai Ming Ting; Takashi Washio; Jonathan R. Wells; Sunil Aryal (Mach. Learn., 2017)

Isolation-based anomaly detection using nearest-neighbor ensembles. - Tharindu R. Bandaragoda; Kai Ming Ting; David W. Albrecht; Fei Tony Liu; Ye Zhu 002; Jonathan R. Wells (Comput. Intell., 2018)

A new simple and efficient density estimator that enables fast systematic search. - Jonathan R. Wells; Kai Ming Ting (Pattern Recognit. Lett., 2019)

Clustering based on Point-Set Kernel. - Kai Ming Ting; Jonathan R. Wells; Ye Zhu 002 (CoRR, 2020)

Simple supervised dissimilarity measure: Bolstering iForest-induced similarity with class information without learning. - Jonathan R. Wells; Sunil Aryal; Kai Ming Ting (Knowl. Inf. Syst., 2020)

Isolation Kernel Density Estimation. - Kai Ming Ting; Takashi Washio; Jonathan R. Wells; Hang Zhang 003 (ICDM, 2021)

Ensemble of Local Decision Trees for Anomaly Detection in Mixed Data. - Sunil Aryal; Jonathan R. Wells (ECML/PKDD (1), 2021)

Isolation kernel: the X factor in efficient and effective large scale online kernel learning. - Kai Ming Ting; Jonathan R. Wells; Takashi Washio (Data Min. Knowl. Discov., 2021)

Isolation Kernel Estimators. - Kai Ming Ting; Takashi Washio; Jonathan R. Wells; Hang Zhang 003; Ye Zhu 002 (Knowl. Inf. Syst., 2023)

Point-Set Kernel Clustering. - Kai Ming Ting; Jonathan R. Wells; Ye Zhu 002 (IEEE Trans. Knowl. Data Eng., 2023)

Enabling clustering algorithms to detect clusters of varying densities through scale-invariant data preprocessing. - Sunil Aryal; Jonathan R. Wells; Arbind Agrahari Baniya; KC Santosh (CoRR, 2024)

Handling Incomplete Heterogeneous Data using a Data-Dependent Kernel. - Youran Zhou; Mohamed Reda Bouadjenek; Jonathan R. Wells; Sunil Aryal (CoRR, 2025)