13 citations · 20 across the 5 of their papers we have counts for
5 papers
On the Structural Limits of Machine Learning Decision Systems: An Information-Theoretic, Interaction-Based, and Stochastic-Dynamical Perspective
Nestor R. Barraza, Gabriel Pena
Machine learning procedures are commonly evaluated in terms of predictive accuracy and computational efficiency. However, their achievable performance is fundamentally constrained…
A non-homogeneous Markov early epidemic growth dynamics model. Application to the SARS-CoV-2 pandemic
Nestor R. Barraza, Gabriel Pena, Verónica Moreno
This work introduces a new markovian stochastic model that can be described as a non-homogeneous Pure Birth process. We propose a functional form of birth rate that depends on the…
A non-homogeneous, non-stationary and path-dependent Markov anomalous diffusion model
Nestor Barraza, Gabriel Pena, Juliana Gambini +1
A novel probabilistic framework for modelling anomalous diffusion is presented. The resulting process is Markovian, non-homogeneous, non-stationary, non-ergodic, and state-dependen…
Measuring COVID-19 spreading speed through the mean time between infections indicator
Gabriel Pena, Verónica Moreno, Nestor Barraza
We propose to use the mean time between infections (MTBI) metric as obtained from a recently introduced non-homogeneous Markov stochastic model. Different types of parameter calibr…
The large-scale structure from non-Gaussian primordial perturbations
G. A. Peña, G. N. Candlish
The late-time effect of primordial non-Gaussianity offers a window into the physics of inflation and the very early Universe. In this work we study the consequences of a particular…