Software tools
POMDPs with Reveals
[code]
Related paper: Revelations: A Decidable Class of POMDPs with Omega-Regular Objectives, 39th Annual AAAI Conference on Artificial Intelligence (AAAI 2025). Implementation accompanying work on revealing POMDPs, with algorithms for weakly and strongly revealing POMDPs that reduce the analysis to a finite belief-support Markov decision process.
Related paper: Revelations: A Decidable Class of POMDPs with Omega-Regular Objectives, 39th Annual AAAI Conference on Artificial Intelligence (AAAI 2025). Implementation accompanying work on revealing POMDPs, with algorithms for weakly and strongly revealing POMDPs that reduce the analysis to a finite belief-support Markov decision process.
Bolt (Blazingly Fast LTL\(_f\) Learning), with an LTL\(_f\) learning benchmark suite
[code]
[DOI]
Related paper: LTL\(_f\) Learning Meets Boolean Set Cover, 32nd International Conference on Tools and Algorithms for the Construction and Analysis of Systems (TACAS 2026). Software and benchmark suite for learning LTL\(_f\) specifications via Boolean set cover.
Related paper: LTL\(_f\) Learning Meets Boolean Set Cover, 32nd International Conference on Tools and Algorithms for the Construction and Analysis of Systems (TACAS 2026). Software and benchmark suite for learning LTL\(_f\) specifications via Boolean set cover.
Regular Memory Requirements
[code]
Related paper: How to Play Optimally for Regular Objectives?, 50th EATCS International Colloquium on Automata, Languages and Programming (ICALP 2023). Algorithms that compute minimal memory structures to play optimally in two-player zero-sum games with regular reachability and safety objectives.
Related paper: How to Play Optimally for Regular Objectives?, 50th EATCS International Colloquium on Automata, Languages and Programming (ICALP 2023). Algorithms that compute minimal memory structures to play optimally in two-player zero-sum games with regular reachability and safety objectives.
Mask R-CNN in OCaml's Owl
[code]
Implementation and optimisation of the Mask R-CNN architecture for image segmentation and classification using OCaml's numerical library Owl. Work produced during an internship at OCaml Labs, University of Cambridge. See my internship report for more details.
Implementation and optimisation of the Mask R-CNN architecture for image segmentation and classification using OCaml's numerical library Owl. Work produced during an internship at OCaml Labs, University of Cambridge. See my internship report for more details.