Patient Risk Assessment and Warning Symptom Detection Using Deep Attention-Based Neural Networks. - Ivan Girardi; Pengfei Ji; An-phi Nguyen; Nora Hollenstein; Adam Ivankay; Lorenz Kuhn; Chiara Marchiori; Ce Zhang 001 (Louhi@EMNLP, 2018)

edGNN: a Simple and Powerful GNN for Directed Labeled Graphs. - Guillaume Jaume; An-phi Nguyen; María Rodríguez Martínez; Jean-Philippe Thiran; Maria Gabrani (CoRR, 2019)

MonoNet: Towards Interpretable Models by Learning Monotonic Features. - An-phi Nguyen; María Rodríguez Martínez (CoRR, 2019)

On quantitative aspects of model interpretability. - An-phi Nguyen; María Rodríguez Martínez (CoRR, 2020)

Learning Invariances for Interpretability using Supervised VAE. - An-phi Nguyen; María Rodríguez Martínez (CoRR, 2020)

It's FLAN time! Summing feature-wise latent representations for interpretability. - An-phi Nguyen; María Rodríguez Martínez (CoRR, 2021)

DECODE: a computational pipeline to discover T cell receptor binding rules. - Iliana Papadopoulou; An-Phi Nguyen; Anna Weber; María Rodríguez Martínez (Bioinform., 2022)

Uncovering Unique Concept Vectors through Latent Space Decomposition. - Mara Graziani; Laura O'Mahony; An-Phi Nguyen; Henning Müller; Vincent Andrearczyk (Trans. Mach. Learn. Res., 2023)

FLAN: feature-wise latent additive neural models for biological applications. - An-phi Nguyen; Stefania Vasilaki; María Rodríguez Martínez (Briefings Bioinform., 2023)