C. Hocquette, A. Niskanen, M Järvisalo, and Andrew Cropper, Learning MDL Logic Programs From Noisy Data, AAAI24.
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Updated
Feb 16, 2024 - Prolog
C. Hocquette, A. Niskanen, M Järvisalo, and Andrew Cropper, Learning MDL Logic Programs From Noisy Data, AAAI24.
A code base for Automated Relational Feature Engineering
Formal verifiaction personal notes
Source code related to the ILP 2019 paper 'LazyBum: Decision tree learning using lazy propositionalization'
This repo contains my undergraduate thesis work where I tried to combine ILP with MaxEnt.
BotGNN: Inclusion of Domain-Knowledge into GNNs using Mode-Directed Inverse Entailment
A grammar and linter for ILP datasets.
Exploit ILP to learn symmetry breaking constraints of ASP programs.
Julia package for fetching and using srlearn-compatible relational datasets.
Active Inductive Logic Programming for Code Search (ICSE 2019)
Vertex-Enriched Graph Neural Network (VEGNN)
Project about experiments of the use of ILASP as a post-hoc method over black-box models, in which we also study and approach technical issues like exponential time execution.
Me and another student at Unibo developed a solution entirely written in Prolog to the game proposed in the following website: https://www.codingame.com/training/hard/vox-codei-episode-1. The report.pdf stands in for the README file.
A MAS system for ethical monitoring and evaluation of dialog systems
srlearn-compatible relational datasets
C. Hocquette, A. Niskanen, R. Morel, M. Järvisalo, and A. Cropper, Learning big logical rules by joining small rules, IJCAI, 2024.
A system to learn first-order logic based chess tactics from human gameplay data using inductive logic programming.
Graduate Level Functional Programming in Racket and Scheme
C. Hocquette and A. Cropper, Relational program synthesis with numerical reasoning, AAAI23.
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