9 citations · 9 across the 3 of their papers we have counts for
4 papers
From Simulated Fluids to Living Tissue: Zero-Shot Foundation Model Transfer to Perturbed Embryos
Louisa Cornelis, Haewon Jeong, Irina Espejo +1
Morphogenesis is driven by the interplay of genetic regulation and tissue mechanics. In vivo video data is limited, particularly under genetic mutations and environmental perturbat…
OgBench: A Framework for Evaluating Graph Neural Networks on Omics Data
Louisa Cornelis, Johan Mathe, Louis Van Langendonck +2
Graph Neural Networks (GNNs) have become the dominant framework for inductive graph-level learning. Yet most benchmarks focus on the regime , where the number of graphs $n…
When Machine Learning Gets Personal: Evaluating Prediction and Explanation
Louisa Cornelis, Guillermo Bernárdez, Haewon Jeong +1
In high-stakes domains like healthcare, users often expect that sharing personal information with machine learning systems will yield tangible benefits, such as more accurate diagn…
Beyond Euclid: An Illustrated Guide to Modern Machine Learning with Geometric, Topological, and Algebraic Structures
Mathilde Papillon, Sophia Sanborn, Johan Mathe +8
The enduring legacy of Euclidean geometry underpins classical machine learning, which, for decades, has been primarily developed for data lying in Euclidean space. Yet, modern mach…