1 citations · 1 across the 2 of their papers we have counts for
2 papers
stat.ML2021
VACA: Design of Variational Graph Autoencoders for Interventional and Counterfactual Queries
Pablo Sanchez-Martin, Miriam Rateike, Isabel Valera
In this paper, we introduce VACA, a novel class of variational graph autoencoders for causal inference in the absence of hidden confounders, when only observational data and the ca…
cs.LG2019★ 1 cited
Out-of-Sample Testing for GANs
Pablo Sánchez-Martín, Pablo M. Olmos, Fernando Pérez-Cruz
We propose a new method to evaluate GANs, namely EvalGAN. EvalGAN relies on a test set to directly measure the reconstruction quality in the original sample space (no auxiliary net…