Malepathirana, T., Senanayake, D., Gautam, V., Engel, M., Balez, R., Lovelace, M.D., Sundaram, G., Heng, B., Chow, S., Marquis, C. and Guillemin, G.J., 2024. Visualization of incrementally learned projection trajectories for longitudinal data. Scientific Reports, 14(1), p.13558.
Hai-Hang W., Wang, R., Malepathirana T., Oetomo, D.,. and Halgamuge, S., 2024. When To Grow? A Fitting Risk-Aware Policy for Layer Growing in Deep Neural Networks. 38th AAAI Conference on Artificial Intelligence (AAAI-24)
Chen, K., Seneviratne, S., Wang, W., Hu, D., Saha, S., Hasan, T., Rasnayaka, S., Malepathirana, T., Gong, M. and Halgamuge, S. (n.d.). AniFaceDiff: High-Fidelity Face Reenactment via Facial Parametric Conditioned Diffusion Models. ArXiv.
Malepathirana, T., Senanayake, D.,. and Halgamuge, S., 2023. NAPA-VQ: Neighborhood-Aware Prototype Augmentation with Vector Quantization for Continual Learning. Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV).
Saha, S., Perera, R., Seneviratne, S., Malepathirana, T., Rasnayaka, S., Geethika, D., Sim, T. and Halgamuge, S., 2023. Undercover Deepfakes: Detecting Fake Segments in Videos. ICCV 2023 Workshop and Challenge on DeepFake Analysis and Detection.
Malepathirana, T., Senanayake, D., Vidanaarachchi, R., Gautam, V.,& Halgamuge, S. (2022). Dimensionality reduction for visualizing high-dimensional biological data. Biosystems, 220, p.104749.
Ranasinghe, N., Ramanan, A., Fernando, S., Hameed, P.N., Herath, D., Malepathirana, T., Suganthan, P., Niranjan, M. and Halgamuge, S., 2022. Interpretability and accessibility of machine learning in selected food processing, agriculture and health applications. arXiv preprint arXiv:2211.16699.
Malepathirana, T., Senanayake D., Gautam, V., Halgamuge H., Robustness of visualization methods in preserving the continuous and discrete latent structures of high-dimensional single-cell data. In 2021 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB) (pp. 1-9). IEEE.
Malepathirana, T., Senanayake D., and Halgamuge H. "Convolutional Neural Network for complex Multi-Electrode Array signal pattern analysis”, 2020 Deep Learning in Medical Biology Symposium [Abstract]
Malepathirana, T., Senanayake D., Deerasooriya Y., Ooi L. and Halgamuge H. "Analysing Multi-Electrode Array (MEA) data derived from Alzheimer Disease organoids" 2020 Lorne Genome [Abstract]
Malepathirana, T., Perera, R., Abeysinghe, Y., Albar, Y., & Thayasivam, U. (2019, January). Adaptation of Multivariate Concept to Multi-Way Agglomerative Clustering for Hierarchical Aspect Aggregation. In The Thirty-Second International Flairs Conference.
Perera, R., Malepathirana, T., Abeysinghe, Y., Albar, Y., & Thayasivam, U. (2019, January). Amalgamation of general and domain-specific word embeddings for improved hierarchical aspect aggregation. In 2019 IEEE 13th International Conference on Semantic Computing (ICSC) (pp. 55-62). IEEE.
