196 citations · 243 across the 10 of their papers we have counts for
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cs.LG2020★ 1 cited
Learning Invariances for Interpretability using Supervised VAE
An-phi Nguyen, María Rodríguez Martínez
We propose to learn model invariances as a means of interpreting a model. This is motivated by a reverse engineering principle. If we understand a problem, we may introduce inducti…
cs.LG2020★ 14 cited
On quantitative aspects of model interpretability
An-phi Nguyen, María Rodríguez Martínez
Despite the growing body of work in interpretable machine learning, it remains unclear how to evaluate different explainability methods without resorting to qualitative assessment…
q-bio.QM2020★ 1 cited
PaccMann on SARS-CoV-2: Designing antiviral candidates with conditional generative models
Jannis Born, Matteo Manica, Joris Cadow +4
With the fast development of COVID-19 into a global pandemic, scientists around the globe are desperately searching for effective antiviral therapeutic agents. Bridging systems bio…