7 citations · 8 across the 4 of their papers we have counts for
4 papers
Sparsity is All You Need: Rethinking Biological Pathway-Informed Approaches in Deep Learning
Isabella Caranzano, Corrado Pancotti, Cesare Rollo +4
Biologically-informed neural networks typically leverage pathway annotations to enhance performance in biomedical applications. We hypothesized that the benefits of pathway integra…
Sheaf HyperNetworks for Personalized Federated Learning
Bao Nguyen, Lorenzo Sani, Xinchi Qiu +2
Graph hypernetworks (GHNs), constructed by combining graph neural networks (GNNs) with hypernetworks (HNs), leverage relational data across various domains such as neural architect…
Incorporating LLM Priors into Tabular Learners
Max Zhu, Siniša Stanivuk, Andrija Petrovic +2
We present a method to integrate Large Language Models (LLMs) and traditional tabular data classification techniques, addressing LLMs challenges like data serialization sensitivity…
Interpretable Medical Diagnostics with Structured Data Extraction by Large Language Models
Aleksa Bisercic, Mladen Nikolic, Mihaela van der Schaar +3
Tabular data is often hidden in text, particularly in medical diagnostic reports. Traditional machine learning (ML) models designed to work with tabular data, cannot effectively pr…