Paper Accepted at ICLR 2026!
Proud to share that the work of our GenAI research team was accepted at ICLR 2026.
This work introduces COSMO-INR, a novel complex modulation-based framework to mitigate spectral attenuation, a common phenomenon that degrades INR performance. The work is grounded on a strong theoretical foundation based on Chebyshev polynomial approximations and harmonic distortion analysis.
This includes a thorough experimental analysis on how COSMO-INR significantly outperforms the existing state of the art on numerous tasks, such as image reconstruction, denoising, inpainting, neural radiance fields (NeRF), and 3D object reconstruction.
About ICLR
The International Conference on Learning Representations (ICLR) is a top-tier venue in Artificial Intelligence and learning systems. According to Google Scholar Metrics, ICLR ranks 8th overall across all disciplines and publication types (2nd in the AI category), placing it among the most prestigious and highest-impact publications such as Nature, The Lancet, The New England Journal of Medicine, Science, and CVPR. ICLR records a h5-index of 362 and h5-median of 652, reflecting very strong citation impact and wide research influence.
Entirely Home-Grown Research at UoP
The achievement is especially meaningful because the research was led entirely by recent graduates and faculty from the Department of Electrical & Electronic Engineering, University of Peradeniya, through the MARC (Multidisciplinary AI Research Centre) INR team. From idea to implementation and writing, the work was developed locally, showcasing the strength of home-grown talent and mentorship at UoP in producing globally competitive AI research.
Team Members
- Pandula Thennakoon
- Avishka Ranasinghe
- Mario De Silva
- Buwaneka Epakanda
Supervisors
- Roshan Godaliyadda
- Parakrama Ekanayake
- Vijitha Herath