Shamane Siriwardhana
Shamane Siriwardhana
Other namesShamane Siri
Marigold | The University of Auckland
Verified email at - Homepage
Cited by
Cited by
Jointly fine-tuning" bert-like" self supervised models to improve multimodal speech emotion recognition
S Siriwardhana, A Reis, R Weerasekera, S Nanayakkara
arXiv preprint arXiv:2008.06682, 2020
Multimodal emotion recognition with transformer-based self supervised feature fusion
S Siriwardhana, T Kaluarachchi, M Billinghurst, S Nanayakkara
IEEE Access 8, 176274-176285, 2020
Fingerreader2. 0: Designing and evaluating a wearable finger-worn camera to assist people with visual impairments while shopping
R Boldu, A Dancu, DJC Matthies, T Buddhika, S Siriwardhana, ...
Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous …, 2018
Vusfa: Variational universal successor features approximator to improve transfer drl for target driven visual navigation
S Siriwardhana, R Weerasakera, DJC Matthies, S Nanayakkara
arXiv preprint arXiv:1908.06376, 2019
Target driven visual navigation with hybrid asynchronous universal successor representations
S Siriwardhana, R Weerasekera, S Nanayakkara
arXiv preprint arXiv:1811.11312, 2018
Improving the Domain Adaptation of Retrieval Augmented Generation (RAG) Models for Open Domain Question Answering
S Siriwardhana, R Weerasekera, E Wen, T Kaluarachchi, R Rana, ...
arXiv preprint arXiv:2210.02627, 2022
Fine-tune the Entire RAG Architecture (including DPR retriever) for Question-Answering
S Siriwardhana, R Weerasekera, E Wen, S Nanayakkara
arXiv preprint arXiv:2106.11517, 2021
A Corneal Surface Reflections-Based Intelligent System for Lifelogging Applications
T Kaluarachchi, S Siriwardhana, E Wen, S Nanayakkara
International Journal of Human–Computer Interaction, 1-18, 2023
VRhook: A Data Collection Tool for VR Motion Sickness Research
E Wen, TI Kaluarachchi, S Siriwardhana, V Tang, M Billinghurst, ...
Proceedings of the 35th Annual ACM Symposium on User Interface Software and …, 2022
Fuse and Adapt: Investigating the Use of Pre-Trained Self-Supervising Learning Models in Limited Data NLU problems
S Siriwardhana
PhD Thesis-University of Auckland, 2022
Universal Successor Features Based Deep Reinforcement Learning for Navigation
S Siriwardhana
Masters Thesis, 2019
VUSFA: Variational Universal Successor Features Approximator
S Siriwardhana, R Weerasakera, DJC Matthies, S Nanayakkara
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