3 papers
cs.LG2026
Classifying Directional Trajectories Near Criticality in the Three-State Majority-Vote Model with Deep Belief Networks and Bidirectional GRUs
Mauricio A. Valle, Gonzalo A. Ruz
In this work, we investigate whether the latent representations learned by a Deep Belief Network (DBN) and a Bidirectional Gated Recurrent Unit (Bi-GRU) can discriminate among four…
cs.LG2026
Exploration of the generative capabilities of Boltzmann machines applied to social systems under the majority rule
Mauricio A. Valle, Gonzalo A. Ruz
We study the generative capabilities of Boltzmann machines to recover systems governed by the majority rule under critical conditions. To this end, we train deep belief networks (D…
cs.LG2024
Physics-informed neural networks for operator equations with stochastic data
Paul Escapil-Inchauspé, Gonzalo A. Ruz
We consider the computation of statistical moments to operator equations with stochastic data. We remark that application of PINNs -- referred to as TPINNs -- allows to solve the i…