3 papers
cs.LG2025
ProteinPNet: Prototypical Part Networks for Concept Learning in Spatial Proteomics
Louis McConnell, Jieran Sun, Theo Maffei +2
Understanding the spatial architecture of the tumor microenvironment (TME) is critical to advance precision oncology. We present ProteinPNet, a novel framework based on prototypica…
cs.LG2025
Meta Learning not to Learn: Robustly Informing Meta-Learning under Nuisance-Varying Families
Louis McConnell
In settings where both spurious and causal predictors are available, standard neural networks trained under the objective of empirical risk minimization (ERM) with no additional in…
cs.LG2024
Counterfactual Generative Modeling with Variational Causal Inference
Yulun Wu, Louie McConnell, Claudia Iriondo
Estimating an individual's counterfactual outcomes under interventions is a challenging task for traditional causal inference and supervised learning approaches when the outcome is…