| AAAI 2026 | Symmetry breaking for inductive logic programming
Cropper, Cerna, and Järvisalo |
| AAAI 2026 | Efficient rule induction by ignoring pointless rules
Cropper and Cerna |
| AAAI 2026 | Can humans teach machines to code?
Hocquette, Langer, Cropper, and Schmid |
| Arxiv | Honey, I shrunk the hypothesis space (through logical preprocessing)
Cropper, Gouveia, and Cerna |
| Arxiv | Learning logical rules using minimum message length
Sharma, Dumancic, King, and Cropper |
| Arxiv | Symbolic snapshot ensembles
Liu and Cropper |
| Arxiv | An empirical comparison of cost functions in inductive logic programming
Hocquette and Cropper |
| IJCAI 2025 | Relational decomposition for program synthesis
Hocquette and Cropper |
| AAAI 2025 | Scalable knowledge refactoring using constrained optimisation
Liu, Cerna, Gouveia, and Cropper |
| Nature Comms 2024 | Symbolic metaprogram search improves learning efficiency and explains rule learning in humans
Rule, Piantadosi, Cropper, Ellis, Nye, and Tenenbaum |
| ECAI 2024 | Learning logic programs by finding minimal unsatisfiable subprograms
Cropper and Hocquette |
| IJCAI 2024 | Learning big logical rules by joining small rules
Hocquette, Niskanen, Morel, Järvisalo, and Cropper |
| IJCAI 2024 | Learning logic programs by discovering higher-order abstractions
Hocquette, Dumančić, and Cropper |
| AAAI 2024 | Learning MDL logic programs from noisy data
Hocquette, Niskanen, Järvisalo, and Cropper |
| AAAI 2024 | Generalisation through negation and predicate invention
Cerna and Cropper |
| ECAI 2023 | Learning logic programs by combining programs
Cropper and Hocquette |
| AAAI 2023 | Relational program synthesis with numerical reasoning
Hocquette and Cropper |
| AAAI 2023 | Learning logic programs by discovering where not to search
Cropper and Hocquette |
| AAAI 2023 | The automatic computer scientist
Cropper |
| MLJ 2023 | Learning programs by explaining failures
Morel and Cropper |
| MLJ 2023 | Learning programs with magic values
Hocquette and Cropper |
| AAAI 2022 | Learning logic programs through divide, constrain, and conquer
Cropper |
| JAIR 2022 | Inductive logic programming at 30: a new introduction
Cropper and Dumančić |
| MLJ 2022 | Inductive logic programming at 30
Cropper, Dumančić, Evans, and Muggleton |
| AAAI 2021 | Knowledge refactoring for inductive program synthesis
Dumančić, Guns, and Cropper |
| MLJ 2021 | Learning programs by learning from failures
Cropper and Morel |
| IJCAI 2020 | Learning large logic programs by going beyond entailment
Cropper and Dumančić |
| IJCAI 2020 | Turning 30: new ideas in inductive logic programming
Cropper, Dumančić, and Muggleton |
| AAAI 2020 | Forgetting to learn logic programs
Cropper |
| AAAI 2020 | Learning higher-order programs through predicate invention
Cropper, Morel, and Muggleton |
| MLJ 2020 | Inductive general game playing
Cropper, Evans, and Law |
| MLJ 2020 | Logical reduction of metarules
Cropper and Tourret |
| MLJ 2020 | Learning higher-order logic programs
Cropper, Morel, and Muggleton |
| IJCAI 2019 | Playgol: learning programs through play
Cropper |
| JELIA 2019 | SLD-resolution reduction of second-order Horn fragments
Tourret and Cropper |
| JELIA 2019 | Typed meta-interpretive learning of logic programs
Morel, Cropper, and Ong |
| MLJ 2019 | Learning efficient logic programs
Cropper and Muggleton |
| ILP 2018 | Derivation reduction of metarules in meta-interpretive learning
Cropper and Tourret |
| IJCAI 2016 | Learning higher-order logic programs through abstraction and invention
Cropper and Muggleton |
| IJCAI 2016 | Logic-based inductive synthesis of efficient programs
Cropper |
| IJCAI 2015 | Learning efficient logical robot strategies involving composable objects
Cropper and Muggleton |
| IJCAI 2015 | Learning efficient logic programs
Cropper |
| ILP 2015 | Meta-interpretive learning of data transformation programs
Cropper, Tamaddoni-Nezhad, and Muggleton |
| ILP 2015 | Typed meta-interpretive learning for proof strategies
Farquhar, Grov, Cropper, Muggleton, and Bundy |
| SCAI 2015 | Can predicate invention compensate for incomplete background knowledge?
Cropper and Muggleton |
| ILP 2014 | Logical minimisation of meta-rules within meta-interpretive learning
Cropper and Muggleton |
