Enes Makalic

42 papers A 1B 2Journal 14Unranked 25
YearRankTypeTitle / Venue / Authors
2026 J jnl
Non-iterative and uncertainty-aware MRI-based liver fat estimation using an unsupervised deep learning method.
Medical Image Anal.
Juan P. Meneses, Cristian Tejos, Enes Makalic, Sergio Uribe
2025 J jnl
A survey on deep learning for polygenic risk scores.
Briefings Bioinform.
Max Schuran, Benjamin Goudey, Gillian S. Dite, Enes Makalic
2025 J jnl
Impact of missing electronic fetal monitoring signals on perinatal asphyxia: a multicohort analysis.
npj Digit. Medicine
Debjyoti Karmakar, Lochana Mendis, Emerson Keenan, Marimuthu Palaniswami, Roxanne Hastie, Enes Makalic, Fiona C. Brownfoot
2025 — conf
Minimum Message Length t-Test.
AI (2)
Enes Makalic, Daniel F. Schmidt
2024 — conf
Bayesian Parametric Proportional Hazards Regression with the Fused Lasso.
AI (2)
Enes Makalic, Daniel F. Schmidt
2023 J jnl
Maximum likelihood estimation of the Weibull distribution with reduced bias.
Stat. Comput.
Enes Makalic, Daniel F. Schmidt
2023 — conf
Minimum Message Length Inference of the Weibull Distribution with Complete and Censored Data.
AI (1)
Enes Makalic, Daniel F. Schmidt
2022 J jnl
An efficient algorithm for sampling from sin
Commun. Stat. Simul. Comput.
Enes Makalic, Daniel F. Schmidt
2022 — conf
Sparse Horseshoe Estimation via Expectation-Maximisation.
ECML/PKDD (5)
Shu Yu Tew, Daniel F. Schmidt, Enes Makalic
2022 J jnl
Sparse Horseshoe Estimation via Expectation-Maximisation.
CoRR
Shu Yu Tew, Daniel F. Schmidt, Enes Makalic
2021 J jnl
Minimum Message Length Inference of the Exponential Distribution with Type I Censoring.
Entropy
Enes Makalic, Daniel Francis Schmidt
2019 — conf
Bayesian Generalized Horseshoe Estimation of Generalized Linear Models.
ECML/PKDD (2)
Daniel F. Schmidt, Enes Makalic
2018 J jnl
Adaptive Bayesian Shrinkage Estimation Using Log-Scale Shrinkage Priors.
CoRR
Daniel F. Schmidt, Enes Makalic
2017 — conf
Robust Lasso Regression with Student-t Residuals.
Australasian Conference on Artificial Intelligence
Daniel F. Schmidt, Enes Makalic
2016 J jnl
A Simple Sampler for the Horseshoe Estimator.
IEEE Signal Process. Lett.
Enes Makalic, Daniel F. Schmidt
2016 — conf
Approximating Message Lengths of Hierarchical Bayesian Models Using Posterior Sampling.
Australasian Conference on Artificial Intelligence
Daniel F. Schmidt, Enes Makalic, John L. Hopper
2016 — conf
Bayesian Grouped Horseshoe Regression with Application to Additive Models.
Australasian Conference on Artificial Intelligence
Zemei Xu, Daniel F. Schmidt, Enes Makalic, Guoqi Q. Qian, John L. Hopper
2016 — conf
Bayesian Robust Regression with the Horseshoe+ Estimator.
Australasian Conference on Artificial Intelligence
Enes Makalic, Daniel F. Schmidt, John L. Hopper
2015 J jnl
High performance computing enabling exhaustive analysis of higher order single nucleotide polymorphism interaction in Genome Wide Association Studies.
Health Inf. Sci. Syst.
Benjamin Goudey, Mani Abedini, John L. Hopper, Michael Inouye, Enes Makalic, Daniel F. Schmidt, John Wagner, Zeyu Zhou, Justin Zobel, Matthias Reumann
2013 — conf
DEPTH: A Novel Algorithm for Feature Ranking with Application to Genome-Wide Association Studies.
Australasian Conference on Artificial Intelligence
Enes Makalic, Daniel F. Schmidt, John L. Hopper
2013 — conf
Minimum Message Length Ridge Regression for Generalized Linear Models.
Australasian Conference on Artificial Intelligence
Daniel F. Schmidt, Enes Makalic
2012 — conf
MML Logistic Regression with Translation and Rotation Invariant Priors.
Australasian Conference on Artificial Intelligence
Enes Makalic, Daniel F. Schmidt
2012 — conf
Minimum Message Length Inference and Mixture Modelling of Inverse Gaussian Distributions.
Australasian Conference on Artificial Intelligence
Daniel F. Schmidt, Enes Makalic
2012 — conf
Supercomputing enabling exhaustive statistical analysis of genome wide association study data: Preliminary results.
EMBC
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, John Wagner, John L. Hopper
2012 J jnl
The Consistency of MDL for Linear Regression Models With Increasing Signal-to-Noise Ratio.
IEEE Trans. Signal Process.
Daniel Francis Schmidt, Enes Makalic
2011 — conf
A Simple Bayesian Algorithm for Feature Ranking in High Dimensional Regression Problems.
Australasian Conference on Artificial Intelligence
Enes Makalic, Daniel Francis Schmidt
2011 J jnl
Estimating the Order of an Autoregressive Model Using Normalized Maximum Likelihood.
IEEE Trans. Signal Process.
Daniel Francis Schmidt, Enes Makalic
2011 — conf
Logistic Regression with the Nonnegative Garrote.
Australasian Conference on Artificial Intelligence
Enes Makalic, Daniel Francis Schmidt
2011 — conf
MMLD Inference of Multilayer Perceptrons.
Algorithmic Probability and Friends
Enes Makalic, Lloyd Allison
2011 — conf
Minimum Message Length Analysis of the Behrens-Fisher Problem.
Algorithmic Probability and Friends
Enes Makalic, Daniel F. Schmidt
2010 J jnl
Fast Computation of the Kullback-Leibler Divergence and Exact Fisher Information for the First-Order Moving Average Model.
IEEE Signal Process. Lett.
Enes Makalic, Daniel Francis Schmidt
2010 — conf
Review of Modern Logistic Regression Methods with Application to Small and Medium Sample Size Problems.
Australasian Conference on Artificial Intelligence
Enes Makalic, Daniel Francis Schmidt
2010 — conf
The Behaviour of the Akaike Information Criterion When Applied to Non-nested Sequences of Models.
Australasian Conference on Artificial Intelligence
Daniel Francis Schmidt, Enes Makalic
2009 — conf
MML Invariant Linear Regression.
Australasian Conference on Artificial Intelligence
Daniel Francis Schmidt, Enes Makalic
2009 — conf
Towards the Interpretation of Utterance Sequences in a Dialogue System.
SIGDIAL Conference
Ingrid Zukerman, Patrick Ye, Kapil Kumar Gupta, Enes Makalic
2009 J jnl
Universal models for the exponential distribution.
IEEE Trans. Inf. Theory
Daniel Francis Schmidt, Enes Makalic
2008 B conf
A Probabilistic Approach to the Interpretation of Spoken Utterances.
PRICAI
Ingrid Zukerman, Enes Makalic, Michael Niemann, Sarah George
2008 B conf
A Probabilistic Model for Understanding Composite Spoken Descriptions.
PRICAI
Enes Makalic, Ingrid Zukerman, Michael Niemann, Daniel Francis Schmidt
2008 A conf
A spoken language interpretation component for a robot dialogue system.
INTERSPEECH
Enes Makalic, Ingrid Zukerman, Michael Niemann
2008 — conf
Using Probabilistic Feature Matching to Understand Spoken Descriptions.
Australasian Conference on Artificial Intelligence
Ingrid Zukerman, Enes Makalic, Michael Niemann
2007 — conf
Hypothesis Generation and Maintenance in the Interpretation of Spoken Utterances.
Australian Conference on Artificial Intelligence
Michael Niemann, Ingrid Zukerman, Enes Makalic, Sarah George
2003 — conf
MML Classification of Music Genres.
Australian Conference on Artificial Intelligence
Adrian C. Bickerstaffe, Enes Makalic