6 citations · 11 across the 12 of their papers we have counts for
8 papers · 1 filter
A Learning Algorithm for Threshold Boolean Networks with Prescribed Fixed Points
Gonzalo A. Ruz
We present a learning algorithm for inferring threshold Boolean networks (TBNs) with a prescribed set of fixed points. The proposed method employs a custom differentiable loss func…
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…
Geometric Filtering of LLM-Generated Samples for Few-Shot Text Classification
Benjamín Schindler, Gonzalo A. Ruz
Large language models (LLMs) can generate synthetic training data for text classification, but the quality of generated samples is heterogeneous: some fall in correct class regions…
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…
Continuous surrogates versus threshold Boolean networks for modeling Arabidopsis ISR gene regulation
Gonzalo A. Ruz
Gene regulatory network modeling often requires balancing predictive accuracy and mechanistic interpretability. In this work, we compare continuous surrogate models and a discrete…
Baseline-Free Policy Optimization for Neural Combinatorial Optimization
Carlos S. Sepúlveda, Gonzalo A. Ruz
Neural combinatorial optimization (NCO) trains autoregressive policies to solve routing problems. The standard training algorithm, REINFORCE with a rollout baseline, requires maint…
Benchmarking Classical Coverage Path Planning Heuristics on Irregular Hexagonal Grids for Maritime Coverage Scenarios
Carlos S. Sepúlveda, Gonzalo A. Ruz
Coverage path planning on irregular hexagonal grids is relevant to maritime surveillance, search and rescue and environmental monitoring, yet classical methods are often compared o…
Critic-Free Deep Reinforcement Learning for Maritime Coverage Path Planning on Irregular Hexagonal Grids
Carlos S. Sepúlveda, Gonzalo A. Ruz
Maritime surveillance missions, such as search and rescue and environmental monitoring, rely on the efficient allocation of sensing assets over vast and geometrically complex areas…