Sparse Implicit Processes for Approximate Inference. - Simón Rodríguez Santana; Bryan Zaldivar; Daniel Hernández-Lobato (CoRR, 2021)

Function-space Inference with Sparse Implicit Processes. - Simón Rodríguez Santana; Bryan Zaldivar; Daniel Hernández-Lobato (ICML, 2022)

Correcting Model Bias with Sparse Implicit Processes. - Simón Rodríguez Santana; Luis A. Ortega Andrés; Daniel Hernández-Lobato; Bryan Zaldivar (CoRR, 2022)

Adversarial α-divergence minimization for Bayesian approximate inference. - Simón Rodríguez Santana; Daniel Hernández-Lobato (Neurocomputing, 2022)

Deep Variational Implicit Processes. - Luis A. Ortega 001; Simón Rodríguez Santana; Daniel Hernández-Lobato (ICLR, 2023)

Variational Linearized Laplace Approximation for Bayesian Deep Learning. - Luis A. Ortega Andrés; Simón Rodríguez Santana; Daniel Hernández-Lobato (ICML, 2024)

Fixed-Mean Gaussian Processes for Post-hoc Bayesian Deep Learning. - Luis A. Ortega 001; Simón Rodríguez Santana; Daniel Hernández-Lobato (CoRR, 2024)

Personalized pricing decisions through adversarial risk analysis. - Daniel Garcia Rasines; Roi Naveiro; David Ríos Insua; Simón Rodríguez Santana (Int. Trans. Oper. Res., 2025)