5 papers
Empirical Characterization of Learning Geometry in Hybrid Quantum Forecasting Models
Sandra Leticia Juárez-Osorio, Jorge I. Hernandez-Martinez, Jesus Ivan Ruiz-Martinez +2
We characterize the learning dynamics of a compact hybrid quantum forecasting model through comparison with a structurally aligned classical baseline. Using stationary harmonic-mix…
SRGAN-CKAN: Expressive Super-Resolution with Nonlinear Functional Operators under Minimal Resources
Roberto Isai Navaro-Aviña, Eduardo Said Merin-Martinez, Andres Mendez-Vazquez +1
Single-Image Super-Resolution (SISR) aims to reconstruct a High-Resolution (HR) image from a Low-Resolution (LR) observation, a fundamentally ill-posed problem where high-frequency…
LTBs-KAN: Linear-Time B-splines Kolmogorov-Arnold Networks
Eduardo Said Merin-Martinez, Andres Mendez-Vazquez, Eduardo Rodriguez-Tello
Kolmogorov-Arnold Networks (KANs) are a recent neural network architecture offering an alternative to Multilayer Perceptrons (MLPs) with improved explainability and expressibility.…
Graph-Based Deep Learning for Component Segmentation of Maize Plants
J. I. Ruiz-Martinez, A. Mendez-Vazquez, E. Rodriguez-Tello
In precision agriculture, one of the most important tasks when exploring crop production is identifying individual plant components. There are several attempts to accomplish this t…
Fourier Series Guided Design of Quantum Convolutional Neural Networks for Enhanced Time Series Forecasting
Sandra Leticia Juárez Osorio, Mayra Alejandra Rivera Ruiz, Andres Mendez-Vazquez +1
In this study, we apply 1D quantum convolution to address the task of time series forecasting. By encoding multiple points into the quantum circuit to predict subsequent data, each…