3 citations · 3 across the 4 of their papers we have counts for
4 papers
Biologically Informed Deep Neural Networks for Multi-Omic Integration, Pathway Activity Inference and Risk Stratification in Cancer
Pedro Henrique da Costa Avelar, Le Ou-Yang, Min Wu +1
Integrating complex, multi-omics data presents significant challenges. Existing approaches often face a trade-off between model interpretability and representational capacity, with…
Is an Image Also Worth 16x16=256 Superpixels? A Framework for Attentional Image Classification
Pedro Henrique da Costa Avelar, Anderson R. Tavares, Luís C. Lamb
Superpixel-based image classification has traditionally leveraged graph neural networks (GNNs) for processing irregular image representations. Recent advances in computer vision, d…
Incorporating Prior Knowledge in Deep Learning Models via Pathway Activity Autoencoders
Pedro Henrique da Costa Avelar, Min Wu, Sophia Tsoka
Motivation: Despite advances in the computational analysis of high-throughput molecular profiling assays (e.g. transcriptomics), a dichotomy exists between methods that are simple…
Multi-Omic Data Integration and Feature Selection for Survival-based Patient Stratification via Supervised Concrete Autoencoders
Pedro Henrique da Costa Avelar, Roman Laddach, Sophia Karagiannis +2
Cancer is a complex disease with significant social and economic impact. Advancements in high-throughput molecular assays and the reduced cost for performing high-quality multi-omi…