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ORCIDDavid L. Dowe
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- affiliation: Monash University, School of Computer Science
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2020 – today
- 2024
[c48]Sin-Yee Yap, Junn Yong Loo, Chee-Ming Ting, Fuad Noman, Raphaël C.-W. Phan, Adeel Razi, David L. Dowe:
A Deep Probabilistic Spatiotemporal Framework for Dynamic Graph Representation Learning with Application to Brain Disorder Identification. IJCAI 2024: 5353-5361- 2021
- [j18]Zheng Fang
, David L. Dowe, Shelton Peiris, Dedi Rosadi:
Minimum Message Length in Hybrid ARMA and LSTM Model Forecasting. Entropy 23(12): 1601 (2021) - [c47]Yang Duan, Chung-Hsing Yeh, David L. Dowe:
Accounting method selection using neural networks and multi-criteria decision making. HICSS 2021: 1-10 - [i4]Lachlan O'Neill, Simon D. Angus, Satya Borgohain, Nader Chmait, David L. Dowe:
Creating Powerful and Interpretable Models withRegression Networks. CoRR abs/2107.14417 (2021) - [i3]Zheng Fang, David L. Dowe, Shelton Peiris, Dedi Rosadi:
Minimum Message Length Autoregressive Moving Average Model Order Selection. CoRR abs/2110.03250 (2021)
2010 – 2019
- 2019
- [c46]John M. Betts, David L. Dowe, Daniel Guimarans, Daniel Damir Harabor, Heshan Kumarage, Peter J. Stuckey, Michael Wybrow:
Peak-Hour Rail Demand Shifting with Discrete Optimisation. CP 2019: 748-763 - 2018
- [j17]Phillip G. D. Ward, Nicholas J. Ferris, Parnesh Raniga, David L. Dowe, Amanda C. L. Ng, David G. Barnes, Gary F. Egan:
Combining images and anatomical knowledge to improve automated vein segmentation in MRI. NeuroImage 165: 294-305 (2018) - [c45]Yang Duan, Chung-Hsing Yeh, David L. Dowe:
Accounting Results Modelling with Neural Networks: The Case of an International Oil and Gas Company. ICONIP (2) 2018: 275-285 - 2017
- [j16]José Hernández-Orallo, Marco Baroni, Jordi Bieger, Nader Chmait, David L. Dowe, Katja Hofmann, Fernando Martínez-Plumed, Claes Strannegård, Kristinn R. Thórisson:
A New AI Evaluation Cosmos: Ready to Play the Game? AI Mag. 38(3): 66-69 (2017) - [j15]Michael Brand, David L. Dowe:
The IMP game: Learnability, approximability and adversarial learning beyond $$\Sigma^0_1$$. J. Log. Comput. 27(7): 2171-2192 (2017) - [c44]Nader Chmait, David L. Dowe, Yuan-Fang Li, David G. Green:
An Information-Theoretic Predictive Model for the Accuracy of AI Agents Adapted from Psychometrics. AGI 2017: 225-236 - [c43]José Hernández-Orallo, Fernando Martínez-Plumed, Ute Schmid, Michael Siebers, David L. Dowe:
Computer Models Solving Intelligence Test Problems: Progress and Implications (Extended Abstract). IJCAI 2017: 5005-5009 - [c42]Phillip G. D. Ward, Nicholas J. Ferris, Parnesh Raniga, Amanda C. L. Ng, David G. Barnes, David L. Dowe, Gary F. Egan:
Vein segmentation using shape-based Markov Random Fields. ISBI 2017: 1133-1136 - 2016
- [j14]José Hernández-Orallo, Fernando Martínez-Plumed, Ute Schmid, Michael Siebers, David L. Dowe:
Computer models solving intelligence test problems: Progress and implications. Artif. Intell. 230: 74-107 (2016) - [c41]Nader Chmait, David L. Dowe, Yuan-Fang Li, David G. Green, Javier Insa-Cabrera:
Factors of Collective Intelligence: How Smart Are Agent Collectives? ECAI 2016: 542-550 - [i2]Michael Brand, David L. Dowe:
The IMP game: Learnability, approximability and adversarial learning beyond $Σ^0_1$. CoRR abs/1602.02743 (2016) - 2015
- [c40]Nader Chmait, David L. Dowe, David G. Green, Yuan-Fang Li:
Observation, Communication and Intelligence in Agent-Based Systems. AGI 2015: 50-59 - [c39]Vidya Saikrishna, David L. Dowe, Sid Ray:
MML inference of Finite State Automata for probabilistic spam detection. ICAPR 2015: 1-6 - 2014
- [j13]David L. Dowe, José Hernández-Orallo:
How universal can an intelligence test be? Adapt. Behav. 22(1): 51-69 (2014) - [j12]José Hernández-Orallo, David L. Dowe, M. Victoria Hernández-Lloreda:
Universal psychometrics: Measuring cognitive abilities in the machine kingdom. Cogn. Syst. Res. 27: 50-74 (2014) - [j11]Yuan-Fang Li, Paramjit K. Das, David L. Dowe:
Two decades of Web application testing - A survey of recent advances. Inf. Syst. 43: 20-54 (2014) - 2013
- [j10]José Hernández-Orallo, David L. Dowe:
On Potential Cognitive Abilities in the Machine Kingdom. Minds Mach. 23(2): 179-210 (2013) - [c38]Thi Han Kyaw, David L. Dowe:
3D EEG Source Localisation: A Preliminary Investigation Using MML. Australasian Conference on Artificial Intelligence 2013: 74-79 - [e1]David L. Dowe:
Algorithmic Probability and Friends. Bayesian Prediction and Artificial Intelligence - Papers from the Ray Solomonoff 85th Memorial Conference, Melbourne, VIC, Australia, November 30 - December 2, 2011. Lecture Notes in Computer Science 7070, Springer 2013, ISBN 978-3-642-44957-4 [contents] - [i1]David L. Dowe, José Hernández-Orallo:
On the universality of cognitive tests. CoRR abs/1305.1991 (2013) - 2012
- [c37]José Hernández-Orallo, Javier Insa-Cabrera, David L. Dowe, Bill Hibbard:
Turing Tests with Turing Machines. Turing-100 2012: 140-156 - 2011
- [c36]José Hernández-Orallo, David L. Dowe, Sergio España-Cubillo, M. Victoria Hernández-Lloreda, Javier Insa-Cabrera:
On More Realistic Environment Distributions for Defining, Evaluating and Developing Intelligence. AGI 2011: 82-91 - [c35]Javier Insa-Cabrera, David L. Dowe, Sergio España-Cubillo, M. Victoria Hernández-Lloreda, José Hernández-Orallo:
Comparing Humans and AI Agents. AGI 2011: 122-132 - [c34]David L. Dowe, José Hernández-Orallo, Paramjit K. Das:
Compression and Intelligence: Social Environments and Communication. AGI 2011: 204-211 - [c33]David L. Dowe:
Introduction to Ray Solomonoff 85th Memorial Conference. Algorithmic Probability and Friends 2011: 1-36 - [c32]Javier Insa-Cabrera, David L. Dowe, José Hernández-Orallo:
Evaluating a Reinforcement Learning Algorithm with a General Intelligence Test. CAEPIA 2011: 1-11 - 2010
- [j9]José Hernández-Orallo, David L. Dowe:
Measuring universal intelligence: Towards an anytime intelligence test. Artif. Intell. 174(18): 1508-1539 (2010) - [c31]David L. Dowe, Nayyar Abbas Zaidi:
Database Normalization as a By-product of Minimum Message Length Inference. Australasian Conference on Artificial Intelligence 2010: 82-91
2000 – 2009
- 2009
- [c30]Gerhard Visser, David L. Dowe, Imants D. Svalbe:
Information-Theoretic Image Reconstruction and Segmentation from Noisy Projections. Australasian Conference on Artificial Intelligence 2009: 170-179 - [c29]Gerhard Visser, David L. Dowe, Petteri Uotila:
Enhancing MML Clustering Using Context Data with Climate Applications. Australasian Conference on Artificial Intelligence 2009: 350-359 - 2008
- [j8]David L. Dowe:
Foreword re C. S. Wallace. Comput. J. 51(5): 523-560 (2008) - [c28]Andrea Torsello, David L. Dowe:
Learning a Generative Model for Structural Representations. Australasian Conference on Artificial Intelligence 2008: 573-583 - [c27]Andrea Torsello, David L. Dowe:
Supervised learning of a generative model for edge-weighted graphs. ICPR 2008: 1-4 - 2007
- [c26]Gerhard Visser, David L. Dowe:
Minimum Message Length Clustering of Spatially-Correlated Data with Varying Inter-Class Penalties. ACIS-ICIS 2007: 17-22 - [c25]A. P. Dalgleish, David L. Dowe, Imants D. Svalbe:
Tomographic Reconstruction of Images from Noisy Projections - A Preliminary Study. Australian Conference on Artificial Intelligence 2007: 539-548 - [c24]Peter J. Tan, David L. Dowe, Trevor I. Dix:
Building Classification Models from Microarray Data with Tree-Based Classification Algorithms. Australian Conference on Artificial Intelligence 2007: 589-598 - 2006
- [c23]T. Maheswaran, J. G. Sanjayan, David L. Dowe, Peter J. Tan:
MML Mixture Models of Heterogeneous Poisson Processes with Uniform Outliers for Bridge Deterioration. Australian Conference on Artificial Intelligence 2006: 322-331 - [c22]Peter J. Tan, David L. Dowe:
Decision Forests with Oblique Decision Trees. MICAI 2006: 593-603 - 2005
- [c21]Lara Kornienko, David W. Albrecht, David L. Dowe:
A Preliminary MML Linear Classifier Using Principal Components for Multiple Classes. Australian Conference on Artificial Intelligence 2005: 922-926 - [c20]McGregor J. Collie, David L. Dowe, Leigh J. Fitzgibbon:
Stock Market Simulation and Inference Technique. HIS 2005: 534-538 - 2004
- [c19]Peter J. Tan, David L. Dowe:
MML Inference of Oblique Decision Trees. Australian Conference on Artificial Intelligence 2004: 1082-1088 - 2003
- [c18]Peter J. Tan, David L. Dowe:
MML Inference of Decision Graphs with Multi-way Joins and Dynamic Attributes. Australian Conference on Artificial Intelligence 2003: 269-281 - [c17]Yudi Agusta, David L. Dowe:
Unsupervised Learning of Correlated Multivariate Gaussian Mixture Models Using MML. Australian Conference on Artificial Intelligence 2003: 477-489 - 2002
- [c16]Lara Kornienko, David L. Dowe, David W. Albrecht:
Message Length Formulation of Support Vector Machines for Binary Classification - A Preliminary Scheme. Australian Joint Conference on Artificial Intelligence 2002: 119-130 - [c15]Peter J. Tan, David L. Dowe:
MML Inference of Decision Graphs with Multi-way Joins. Australian Joint Conference on Artificial Intelligence 2002: 131-142 - [c14]Yudi Agusta, David L. Dowe:
MML Clustering of Continuous-Valued Data Using Gaussian and t Distributions. Australian Joint Conference on Artificial Intelligence 2002: 143-154 - [c13]Leigh J. Fitzgibbon, David L. Dowe, Lloyd Allison:
Univariate Polynomial Inference by Monte Carlo Message Length Approximation. ICML 2002: 147-154 - [c12]Leigh J. Fitzgibbon, David L. Dowe, Lloyd Allison:
Change-Point Estimation Using New Minimum Message Length Approximations. PRICAI 2002: 244-254 - 2001
- [c11]Scott Needham, David L. Dowe:
Message Length as an Effective Ockham's Razor in Decision Tree Induction. AISTATS 2001: 216-223 - 2000
- [j7]Chris S. Wallace, David L. Dowe:
MML clustering of multi-state, Poisson, von Mises circular and Gaussian distributions. Stat. Comput. 10(1): 73-83 (2000) - [c10]Leigh J. Fitzgibbon, Lloyd Allison, David L. Dowe:
Minimum Message Length Grouping of Ordered Data. ALT 2000: 56-70 - [c9]Anthony R. Jansen, David L. Dowe, Graham E. Farr:
Inductive Inference of Chess Player Strategy. PRICAI 2000: 61-71
1990 – 1999
- 1999
- [j6]Chris S. Wallace, David L. Dowe:
Minimum Message Length and Kolmogorov Complexity. Comput. J. 42(4): 270-283 (1999) - [j5]Chris S. Wallace, David L. Dowe:
Refinements of MDL and MML Coding. Comput. J. 42(4): 330-337 (1999) - [j4]Chris S. Wallace, David L. Dowe:
Rejoinder. Comput. J. 42(4): 345-347 (1999) - [c8]Murlikrishna Viswanathan, Chris S. Wallace, David L. Dowe, Kevin B. Korb:
Finding Cutpoints in Noisy Binary Sequences - A Revised Empirical Evaluation. Australian Joint Conference on Artificial Intelligence 1999: 405-416 - [c7]David L. Dowe, Klaus Prank:
Information Theoretic Approaches to Biology - Session Introduction. Pacific Symposium on Biocomputing 1999: 252-253 - 1998
- [j3]Glen Pringle, Lloyd Allison, David L. Dowe:
What is a Tall Poppy Among Web Pages? Comput. Networks 30(1-7): 369-377 (1998) - [c6]David R. Powell, Lloyd Allison, Trevor I. Dix, David L. Dowe:
Alignment of Low Information Sequences. CATS 1998: 215-230 - [c5]David L. Dowe, Rohan A. Baxter, Jonathan J. Oliver, Chris S. Wallace:
Point Estimation Using the Kullback-Leibler Loss Function and MML. PAKDD 1998: 87-95 - [c4]Russell T. Edwards, David L. Dowe:
Single Factor Analysis in MML Mixture Modelling. PAKDD 1998: 96-109 - [c3]David L. Dowe, Lloyd Allison, Glen Pringle:
The Hunter and the Hunted - Modelling the Relationship Between Web Pages and Search Engines. PAKDD 1998: 380-382 - 1997
- [c2]Chris S. Wallace, David L. Dowe:
MML Mixture Modelling of Multi-state, Poisson, vonMises circular and Gaussian Distributions. AISTATS 1997: 529-536 - 1996
- [c1]David L. Dowe, Jonathan J. Oliver, Chris S. Wallace:
MML Estimation of the Parameters of the Sherical Fisher Distribution. ALT 1996: 213-227 - 1990
- [j2]David L. Dowe:
Can Black Force a Win? J. Int. Comput. Games Assoc. 13(3): 165-166 (1990) - [j1]David L. Dowe, Ingo Althöfer, John Roycroft:
Symmetrical Chess. J. Int. Comput. Games Assoc. 13(4): 235 (1990)
Coauthor Index
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last updated on 2024-10-21 20:30 CEST by the dblp team
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