MML Classification of Music Genres. - Adrian C. Bickerstaffe; Enes Makalic (Australian Conference on Artificial Intelligence, 2003)

Hypothesis Generation and Maintenance in the Interpretation of Spoken Utterances. - Michael Niemann; Ingrid Zukerman; Enes Makalic; Sarah George (Australian Conference on Artificial Intelligence, 2007)

Using Probabilistic Feature Matching to Understand Spoken Descriptions. - Ingrid Zukerman; Enes Makalic; Michael Niemann (Australasian Conference on Artificial Intelligence, 2008)

A spoken language interpretation component for a robot dialogue system. - Enes Makalic; Ingrid Zukerman; Michael Niemann (INTERSPEECH, 2008)

A Probabilistic Model for Understanding Composite Spoken Descriptions. - Enes Makalic; Ingrid Zukerman; Michael Niemann; Daniel Francis Schmidt (PRICAI, 2008)

A Probabilistic Approach to the Interpretation of Spoken Utterances. - Ingrid Zukerman; Enes Makalic; Michael Niemann; Sarah George (PRICAI, 2008)

MML Invariant Linear Regression. - Daniel Francis Schmidt; Enes Makalic (Australasian Conference on Artificial Intelligence, 2009)

Towards the Interpretation of Utterance Sequences in a Dialogue System. - Ingrid Zukerman; Patrick Ye; Kapil Kumar Gupta; Enes Makalic (SIGDIAL Conference, 2009)

Universal models for the exponential distribution. - Daniel Francis Schmidt; Enes Makalic (IEEE Trans. Inf. Theory, 2009)

Review of Modern Logistic Regression Methods with Application to Small and Medium Sample Size Problems. - Enes Makalic; Daniel Francis Schmidt (Australasian Conference on Artificial Intelligence, 2010)

The Behaviour of the Akaike Information Criterion When Applied to Non-nested Sequences of Models. - Daniel Francis Schmidt; Enes Makalic (Australasian Conference on Artificial Intelligence, 2010)

Fast Computation of the Kullback-Leibler Divergence and Exact Fisher Information for the First-Order Moving Average Model. - Enes Makalic; Daniel Francis Schmidt (IEEE Signal Process. Lett., 2010)

Logistic Regression with the Nonnegative Garrote. - Enes Makalic; Daniel Francis Schmidt (Australasian Conference on Artificial Intelligence, 2011)

A Simple Bayesian Algorithm for Feature Ranking in High Dimensional Regression Problems. - Enes Makalic; Daniel Francis Schmidt (Australasian Conference on Artificial Intelligence, 2011)

MMLD Inference of Multilayer Perceptrons. - Enes Makalic; Lloyd Allison (Algorithmic Probability and Friends, 2011)

Minimum Message Length Analysis of the Behrens-Fisher Problem. - Enes Makalic; Daniel F. Schmidt (Algorithmic Probability and Friends, 2011)

Estimating the Order of an Autoregressive Model Using Normalized Maximum Likelihood. - Daniel Francis Schmidt; Enes Makalic (IEEE Trans. Signal Process., 2011)

MML Logistic Regression with Translation and Rotation Invariant Priors. - Enes Makalic; Daniel F. Schmidt (Australasian Conference on Artificial Intelligence, 2012)

Minimum Message Length Inference and Mixture Modelling of Inverse Gaussian Distributions. - Daniel F. Schmidt; Enes Makalic (Australasian Conference on Artificial Intelligence, 2012)

Supercomputing enabling exhaustive statistical analysis of genome wide association study data: Preliminary results. - Matthias Reumann; Enes Makalic; Benjamin W. Goudey; Michael Inouye; Adrian Bickerstaffe; Minh Bui; Daniel J. Park; Miroslaw K. Kapuscinski; Daniel F. Schmidt; Zeyu Zhou; Guoqi Q. Qian; Justin Zobel; et al. (EMBC, 2012)

The Consistency of MDL for Linear Regression Models With Increasing Signal-to-Noise Ratio. - Daniel Francis Schmidt; Enes Makalic (IEEE Trans. Signal Process., 2012)

DEPTH: A Novel Algorithm for Feature Ranking with Application to Genome-Wide Association Studies. - Enes Makalic; Daniel F. Schmidt; John L. Hopper (Australasian Conference on Artificial Intelligence, 2013)

Minimum Message Length Ridge Regression for Generalized Linear Models. - Daniel F. Schmidt; Enes Makalic (Australasian Conference on Artificial Intelligence, 2013)

High performance computing enabling exhaustive analysis of higher order single nucleotide polymorphism interaction in Genome Wide Association Studies. - Benjamin Goudey; Mani Abedini; John L. Hopper; Michael Inouye; Enes Makalic; Daniel F. Schmidt; John Wagner; Zeyu Zhou; Justin Zobel; Matthias Reumann (Health Inf. Sci. Syst., 2015)

Bayesian Robust Regression with the Horseshoe+ Estimator. - Enes Makalic; Daniel F. Schmidt; John L. Hopper (Australasian Conference on Artificial Intelligence, 2016)

Approximating Message Lengths of Hierarchical Bayesian Models Using Posterior Sampling. - Daniel F. Schmidt; Enes Makalic; John L. Hopper (Australasian Conference on Artificial Intelligence, 2016)

Bayesian Grouped Horseshoe Regression with Application to Additive Models. - Zemei Xu; Daniel F. Schmidt; Enes Makalic; Guoqi Q. Qian; John L. Hopper (Australasian Conference on Artificial Intelligence, 2016)

A Simple Sampler for the Horseshoe Estimator. - Enes Makalic; Daniel F. Schmidt (IEEE Signal Process. Lett., 2016)

Robust Lasso Regression with Student-t Residuals. - Daniel F. Schmidt; Enes Makalic (Australasian Conference on Artificial Intelligence, 2017)

Adaptive Bayesian Shrinkage Estimation Using Log-Scale Shrinkage Priors. - Daniel F. Schmidt; Enes Makalic (CoRR, 2018)

Bayesian Generalized Horseshoe Estimation of Generalized Linear Models. - Daniel F. Schmidt; Enes Makalic (ECML/PKDD (2), 2019)

Minimum Message Length Inference of the Exponential Distribution with Type I Censoring. - Enes Makalic; Daniel Francis Schmidt (Entropy, 2021)

Sparse Horseshoe Estimation via Expectation-Maximisation. - Shu Yu Tew; Daniel F. Schmidt; Enes Makalic (ECML/PKDD (5), 2022)

An efficient algorithm for sampling from sink (x) for generating random correlation matrices. - Enes Makalic; Daniel F. Schmidt (Commun. Stat. Simul. Comput., 2022)

Minimum Message Length Inference of the Weibull Distribution with Complete and Censored Data. - Enes Makalic; Daniel F. Schmidt (AI (1), 2023)

Maximum likelihood estimation of the Weibull distribution with reduced bias. - Enes Makalic; Daniel F. Schmidt (Stat. Comput., 2023)

Bayesian Parametric Proportional Hazards Regression with the Fused Lasso. - Enes Makalic; Daniel F. Schmidt (AI (2), 2024)

Impact of missing electronic fetal monitoring signals on perinatal asphyxia: a multicohort analysis. - Debjyoti Karmakar; Lochana Mendis; Emerson Keenan; Marimuthu Palaniswami; Roxanne Hastie; Enes Makalic; Fiona C. Brownfoot (npj Digit. Medicine, 2025)