| Towards modelling active sound localisation based on Bayesian inference in a static environment G McLachlan, P Majdak, J Reijniers, H Peremans Acta Acustica 5, 45, 2021 | 24 | 2021 |
| Dynamic spectral cues do not affect human sound localization during small head movements G McLachlan, P Majdak, J Reijniers, M Mihocic, H Peremans Front. Neurosci. 17, 2023 | 11 | 2023 |
| Assessing the perceived reverberation in different rooms for a set of musical instrument sounds A Osses Vecchi, G McLachlan, A Kohlrausch The Journal of the Acoustical Society of America 148 (1), EL93-EL98, 2020 | 5 | 2020 |
| Ideal versus non-ideal observer models for sound localization H Peremans, G McLACHLAN, P Majdak, J Reijniers Proceedings of the 24th International Congress on Acoustics, 2022 | 1 | 2022 |
| Head rotations follow those of a truncated Fick gimbal during an auditory guided visual search task G McLachlan, P Lladó, H Peremans Journal of Neurophysiology, 2024 | | 2024 |
| Active sound localisation through Bayesian inference GA McLachlan University of Antwerp, 2024 | | 2024 |
| Insights into dynamic sound localisation: A direction-dependent comparison between human listeners and a Bayesian model. GA McLachlan, P Majdak, J Reijniers, M Mihocic, H Peremans bioRxiv, 2024.04. 26.591250, 2024 | | 2024 |
| THREE YEARS OF THE EAA'S YOUNG ACOUSTICIANS NETWORK IN SOCIAL MEDIA EA Raad, M Argotti, S Duran, E Fasllija, T Lobato, G McLachlan, D Pereira, ... Proceedings of Forum Acusticum, 2023 | | 2023 |
| Three Years of the EAA's Young Acousticians Network in Social Media E Abi Raad, M Argotti, S Duran, E Fasllija, THG Lobato, K Loh, ... Universitätsbibliothek der RWTH Aachen, 2023 | | 2023 |
| EFFECTS OF MONAURAL SPECTRAL CUES ON SOUND LOCALISATION DURING SMALL HEAD MOVEMENTS G McLachlan, P Majdak, J Reijniers, M Mihocic, H Peremans | | 2023 |
| Technical Report: SONICOM/IEEE Listener Acoustic Personalisation (LAP) Challenge-2024 M Geronazzo, L Picinali, A Hogg, R Barumerli, K Poole, R Daugintis, ... | | |
| Modelling Dynamic Sound Localisation through Bayesian Inference: A Sensitivity Analysis G McLachlan, H Peremans | | |
