activity
20222026
most citedExplaining Genetic Programming Trees using Large Language Models

7 citations · 8 across the 4 of their papers we have counts for

collaborators

5 papers

cs.SD2026

Single Microphone Own Voice Detection based on Simulated Transfer Functions for Hearing Aids

Mathuranathan Mayuravaani, W. Bastiaan Kleijn, Andrew Lensen +1

This paper presents a simulation-based approach to own voice detection (OVD) in hearing aids using a single microphone. While OVD can significantly improve user comfort and speech…

cs.CV2025

Re-Identifying Kākā with AI-Automated Video Key Frame Extraction

Paula Maddigan, Andrew Lensen, Rachael C. Shaw

Accurate recognition and re-identification of individual animals is essential for successful wildlife population monitoring. Traditional methods, such as leg banding of birds, are…

cs.NE2024★ 7 cited

Explaining Genetic Programming Trees using Large Language Models

Paula Maddigan, Andrew Lensen, Bing Xue

Genetic programming (GP) has the potential to generate explainable results, especially when used for dimensionality reduction. In this research, we investigate the potential of lev…

cs.NE2024★ 1 cited

Genetic Programming for Explainable Manifold Learning

Ben Cravens, Andrew Lensen, Paula Maddigan +1

Manifold learning techniques play a pivotal role in machine learning by revealing lower-dimensional embeddings within high-dimensional data, thus enhancing both the efficiency and…

cs.LG2022

Explainable Artificial Intelligence for Assault Sentence Prediction in New Zealand

Harry Rodger, Andrew Lensen, Marcin Betkier

The judiciary has historically been conservative in its use of Artificial Intelligence, but recent advances in machine learning have prompted scholars to reconsider such use in tas…