Propositional Dynamic Logic (PDL) [1] is a logic in which abstract properties about the behaviour of programs can be expressed, in a very general way. Because of its generality it is suitable for checking the behaviour or a wide range of programs and systems, via model checking. PDL is what is known as a modal … full description “A Cyclic Prover for Propositional Dynamic Logic (available)”
Category: Logic
Predicting and Explaining Drug Toxicity with Graph Neural Networks (available)
This student research project focuses on predicting and explaining drug toxicity using advanced machine learning techniques, specifically Graph Neural Networks (GNNs). Graph Neural Networks are a modern, powerful class of machine learning models widely used across diverse fields, from chemistry to social networks. However, one of the major challenges with traditional GNNs is their “black-box” … full description “Predicting and Explaining Drug Toxicity with Graph Neural Networks (available)”
Teaching Small LLMs to Reason (ongoing)
Large Language Models (LLMs) such as GPT4, are a game-changer for AI. Equipped with hundreds of billions of parameters, and trained on vast amounts of textual data totalling hundreds of terabytes, these models have revolutionised operations across numerous domains. But despite their considerable capabilities, their sheer size often means that they require substantial computational resources … full description “Teaching Small LLMs to Reason (ongoing)”