Parameters Estimation for the Cosmic Microwave Background with Bayesian Neural Networks. - Héctor J. Hortúa; Riccardo Volpi; Dimitri Marinelli; Luigi Malagò (CoRR, 2019)

Parameters Estimation from the 21 cm signal using Variational Inference. - Héctor J. Hortúa; Riccardo Volpi; Luigi Malagò (CoRR, 2020)

Reliable Uncertainties for Bayesian Neural Networks using Alpha-divergences. - Héctor J. Hortúa; Luigi Malagò; Riccardo Volpi (CoRR, 2020)

Accelerating MCMC algorithms through Bayesian Deep Networks. - Héctor J. Hortúa; Riccardo Volpi; Dimitri Marinelli; Luigi Malagò (CoRR, 2020)

Constraining the Reionization History using Bayesian Normalizing Flows. - Héctor J. Hortúa; Luigi Malagò; Riccardo Volpi (Mach. Learn. Sci. Technol., 2020)

Constraining cosmological parameters from N-body simulations with Variational Bayesian Neural Networks. - Héctor J. Hortúa; Luz Ángela García; Leonardo Castañeda C (CoRR, 2023)

Bayesian deep learning for cosmic volumes with modified gravity. - Jorge Enrique García-Farieta; Héctor J. Hortúa; Francisco-Shu Kitaura (CoRR, 2023)

Forecasting VIX using Bayesian Deep Learning. - Héctor J. Hortúa; Andrés Mora-Valencia (CoRR, 2024)

Deep Bayesian segmentation for colon polyps: Well-calibrated predictions in medical imaging. - Daniela L. Ramos; Héctor J. Hortúa (Biomed. Signal Process. Control., 2025)

Enhancing Diagnostic in 3D COVID-19 Pneumonia CT-scans through Explainable Uncertainty Bayesian Quantification. - Juan Manuel Liscano Fierro; Héctor J. Hortúa (CoRR, 2025)

Conditional Diffusion-Flow models for generating 3D cosmic density fields: applications to f(R) cosmologies. - Julieth Katherine Riveros; Paola Saavedra; Héctor J. Hortúa; Jorge Enrique García-Farieta; Iván Olier (CoRR, 2025)