Using Defeasible Logic for a Window on a Probabilistic Database: Some Preliminary Notes. - James Cussens; Anthony Hunter (ECSQARU, 1991)

Using Maximum Entropy in a Defeasible Logic with Probabilistic Semantics. - James Cussens; Anthony Hunter (IPMU, 1992)

Generating Explicit Orderings for Non-monotonic Logics. - James Cussens; Anthony Hunter; Ashwin Srinivasan 001 (AAAI, 1993)

Bayes and Pseudo-Bayes Estimates of Conditional Probabilities and Their Reliability. - James Cussens (ECML, 1993)

A Bayesian Analysis of Algorithms for Learning Finite Functions. - James Cussens (ICML, 1995)

Deduction, induction and probabilistic support. - James Cussens (Synth., 1996)

Part-of-Speech Tagging Using Progol. - James Cussens (ILP, 1997)

Using Prior Probabilities and Density Estimation for Relational Classification. - James Cussens (ILP, 1998)

Morphosyntactic Tagging of Slovene Using Progol. - James Cussens; Saso Dzeroski; Tomaz Erjavec (ILP, 1999)

Experiments in Inductive Chart Parsing. - James Cussens; Stephen G. Pulman (Learning Language in Logic, 1999)

An Introduction to Inductive Logic Programming and Learning Language in Logic. - Saso Dzeroski; James Cussens; Suresh Manandhar (Learning Language in Logic, 1999)

Loglinear models for first-order probabilistic reasoning. - James Cussens (UAI, 1999)

Integrating Probabilistic and Logical Reasoning. - James Cussens (Electron. Trans. Artif. Intell., 1999)

Incorporating Linguistics Constraints into Inductive Logic Programming. - James Cussens; Stephen Pulman (CoNLL/LLL, 2000)

Stochastic Logic Programs: Sampling, Inference and Applications. - James Cussens (UAI, 2000)

Statistical Aspects of Stochastic Logic Programs. - James Cussens (AISTATS, 2001)

Prolog Issues of an MCMC Algorithm. - Nicos Angelopoulos; James Cussens (INAP, 2001)

Prolog Issues and Experimental Results of an MCMC Algorithm. - Nicos Angelopoulos; James Cussens (INAP (LNCS Volume), 2001)

Markov Chain Monte Carlo using Tree-Based Priors on Model Structure. - Nicos Angelopoulos; James Cussens (UAI, 2001)

Parameter Estimation in Stochastic Logic Programs. - James Cussens (Mach. Learn., 2001)

Issues in Learning Language in Logic. - James Cussens (Computational Logic: Logic Programming and Beyond, 2002)

CLP(BN): Constraint Logic Programming for Probabilistic Knowledge. - Vítor Santos Costa; David Page; Maleeha Qazi; James Cussens (UAI, 2003)

At the Interface of Inductive Logic Programming and Statistics. - James Cussens (ILP, 2004)

Exploiting independence for branch operations in Bayesian learning of C&RTs. - Nicos Angelopoulos; James Cussens (Probabilistic, Logical and Relational Learning, 2005)

Tempering for Bayesian C&RT. - Nicos Angelopoulos; James Cussens (ICML, 2005)

Exploiting Informative Priors for Bayesian Classification and Regression Trees. - Nicos Angelopoulos; James Cussens (IJCAI, 2005)

Inductive Mercury Programming. - Barnaby Fisher; James Cussens (ILP, 2006)

Model equivalence of PRISM programs. - James Cussens (Probabilistic, Logical and Relational Learning - A Further Synthesis, 2007)

CLP(BN): Constraint Logic Programming for Probabilistic Knowledge. - Vítor Santos Costa; David Page; James Cussens (Probabilistic Inductive Logic Programming, 2008)

Bayesian network learning by compiling to weighted MAX-SAT. - James Cussens (UAI, 2008)

Bayesian learning of Bayesian networks with informative priors. - Nicos Angelopoulos; James Cussens (Ann. Math. Artif. Intell., 2008)

Searching a Multivariate Partition Space Using MAX-SAT. - Silvia Liverani; James Cussens; Jim Q. Smith (CIBB, 2009)

On Generative Parameterisations of Markov Logic Networks. - James Cussens (MLG/SRL@ILP, 2009)

Discriminative Clustering for Content-Based Tag Recommendation in Social Bookmarking Systems. - Malik Tahir Hassan; Asim Karim; Suresh Manandhar; James Cussens (DC@PKDD/ECML, 2009)

Instruction Cache Prediction Using Bayesian Networks. - Mark Bartlett; Iain Bate; James Cussens (ECAI, 2010)

Maximum likelihood pedigree reconstruction using integer programming. - James Cussens (WCB@ICLP, 2010)

Learning Bayesian Networks for Improved Instruction Cache Analysis. - Mark Bartlett; Iain Bate; James Cussens (ICMLA, 2010)

Approximate Bayesian Computation for the Parameters of PRISM Programs. - James Cussens (ILP, 2010)

Induction. - James Cussens (Encyclopedia of Machine Learning, 2010)

Learning a Generative Failure-Free PRISM Clause. - Waleed Alsanie; James Cussens (ILP (Late Breaking Papers), 2011)

Probabilistic Instruction Cache Analysis Using Bayesian Networks. - Mark Bartlett; Iain Bate; James Cussens; Dimitar Kazakov (RTCSA (1), 2011)

Bayesian network learning with cutting planes. - James Cussens (UAI, 2011)

Online Bayesian inference for the parameters of PRISM programs. - James Cussens (Mach. Learn., 2012)

Advances in Bayesian Network Learning using Integer Programming. - James Cussens; Mark Bartlett (UAI, 2013)

First-order integer programming for MAP problems. - James Cussens (CoRR, 2015)

Learning failure-free PRISM programs. - Waleed Alsanie; James Cussens (Int. J. Approx. Reason., 2015)

Introduction to the special issue on probability, logic and learning. - James Cussens; Luc De Raedt; Angelika Kimmig; Taisuke Sato (Theory Pract. Log. Program., 2015)

The Chordal Graph Polytope for Learning Decomposable Models. - Milan Studený; James Cussens (Probabilistic Graphical Models, 2016)

Exact estimation of multiple directed acyclic graphs. - Chris J. Oates; Jim Q. Smith; Sach Mukherjee; James Cussens (Stat. Comput., 2016)

Bayesian Network Structure Learning with Integer Programming: Polytopes, Facets and Complexity (Extended Abstract). - James Cussens; Matti Järvisalo; Janne H. Korhonen; Mark Bartlett (IJCAI, 2017)

Integer Linear Programming for the Bayesian network structure learning problem. - Mark Bartlett; James Cussens (Artif. Intell., 2017)

Distributional logic programming for Bayesian knowledge representation. - Nicos Angelopoulos; James Cussens (Int. J. Approx. Reason., 2017)

Towards using the chordal graph polytope in learning decomposable models. - Milan Studený; James Cussens (Int. J. Approx. Reason., 2017)

Bayesian Network Structure Learning with Integer Programming: Polytopes, Facets and Complexity. - James Cussens; Matti Järvisalo; Janne H. Korhonen; Mark Bartlett (J. Artif. Intell. Res., 2017)

Polyhedral aspects of score equivalence in Bayesian network structure learning. - James Cussens; David Haws; Milan Studený (Math. Program., 2017)

Induction. - James Cussens (Encyclopedia of Machine Learning and Data Mining, 2017)

Markov Random Field MAP as Set Partitioning. - James Cussens (PGM, 2018)

Finding Minimal Cost Herbrand Models with Branch-Cut-and-Price. - James Cussens (CoRR, 2018)

Probabilistic logic programming (PLP) 2016. - Arjen Hommersom; James Cussens (Int. J. Approx. Reason., 2018)

Preface to the special issue on inductive logic programming. - James Cussens; Alessandra Russo (Mach. Learn., 2018)

Finding All Bayesian Network Structures within a Factor of Optimal. - Zhenyu A. Liao; Charupriya Sharma; James Cussens; Peter van Beek (AAAI, 2019)

Online Causal Structure Learning in the Presence of Latent Variables. - Durdane Kocacoban; James Cussens (ICMLA, 2019)

Kernel-based Approach to Handle Mixed Data for Inferring Causal Graphs. - Teny Handhayani; James Cussens (CoRR, 2019)

On Pruning for Score-Based Bayesian Network Structure Learning. - Alvaro Henrique Chaim Correia; James Cussens; Cassio P. de Campos (AISTATS, 2020)

GOBNILP: Learning Bayesian network structure with integer programming. - James Cussens (PGM, 2020)

Kernel-based Approach for Learning Causal Graphs from Mixed Data. - Teny Handhayani; James Cussens (PGM, 2020)

A Score-and-Search Approach to Learning Bayesian Networks with Noisy-OR Relations. - Charupriya Sharma; Zhenyu A. Liao; James Cussens; Peter van Beek (PGM, 2020)

Dual Formulation of the Chordal Graph Conjecture. - Milan Studený; James Cussens; Václav Kratochvíl (PGM, 2020)

Learning All Credible Bayesian Network Structures for Model Averaging. - Zhenyu A. Liao; Charupriya Sharma; James Cussens; Peter van Beek (CoRR, 2020)

The dual polyhedron to the chordal graph polytope and the rebuttal of the chordal graph conjecture. - Milan Studený; James Cussens; Václav Kratochvíl (Int. J. Approx. Reason., 2021)

Branch-Price-and-Cut for Causal Discovery. - James Cussens (CLeaR, 2023)