32 citations · 34 across the 7 of their papers we have counts for
8 papers
Graph-Eq: Discovering Mathematical Equations using Graph Generative Models
Nisal Ranasinghe, Damith Senanayake, Saman Halgamuge
The ability to discover meaningful, accurate, and concise mathematical equations that describe datasets is valuable across various domains. Equations offer explicit relationships b…
Arch-VQ: Discrete Architecture Representation Learning with Autoregressive Priors
Deshani Geethika Poddenige, Sachith Seneviratne, Asela Hevapathige +4
Existing neural architecture representation learning methods focus on continuous representation learning, typically using Variational Autoencoders (VAEs) to map discrete architectu…
Day-ahead regional solar power forecasting with hierarchical temporal convolutional neural networks using historical power generation and weather data
Maneesha Perera, Julian De Hoog, Kasun Bandara +2
Regional solar power forecasting, which involves predicting the total power generation from all rooftop photovoltaic systems in a region holds significant importance for various st…
When To Grow? A Fitting Risk-Aware Policy for Layer Growing in Deep Neural Networks
Haihang Wu, Wei Wang, Tamasha Malepathirana +3
Neural growth is the process of growing a small neural network to a large network and has been utilized to accelerate the training of deep neural networks. One crucial aspect of ne…
GINN-LP: A Growing Interpretable Neural Network for Discovering Multivariate Laurent Polynomial Equations
Nisal Ranasinghe, Damith Senanayake, Sachith Seneviratne +2
Traditional machine learning is generally treated as a black-box optimization problem and does not typically produce interpretable functions that connect inputs and outputs. Howeve…
NAPA-VQ: Neighborhood Aware Prototype Augmentation with Vector Quantization for Continual Learning
Tamasha Malepathirana, Damith Senanayake, Saman Halgamuge
Catastrophic forgetting; the loss of old knowledge upon acquiring new knowledge, is a pitfall faced by deep neural networks in real-world applications. Many prevailing solutions to…
DALLE-URBAN: Capturing the urban design expertise of large text to image transformers
Sachith Seneviratne, Damith Senanayake, Sanka Rasnayaka +2
Automatically converting text descriptions into images using transformer architectures has recently received considerable attention. Such advances have implications for many applie…
Self Organizing Nebulous Growths for Robust and Incremental Data Visualization
Damith Senanayake, Wei Wang, Shalin H. Naik +1
Non-parametric dimensionality reduction techniques, such as t-SNE and UMAP, are proficient in providing visualizations for datasets of fixed sizes. However, they cannot incremental…