2 citations · 2 across the 7 of their papers we have counts for
7 papers
Constructive interpolation and generalization rates for neural ODEs: a control perspective
Antonio Álvarez-López, Lorenzo Liverani, Enrique Zuazua
We study supervised regression with neural ODEs (NODEs) from a control-theoretic perspective to derive explicit population-risk bounds. We focus on a widely used class of non-auton…
Gaussian mixture models in Hilbert spaces via kernel methods
Daniel López-Montero, Antonio Álvarez-López, Marcos Matabuena
Modern datasets across many disciplines increasingly consist of time-evolving, potentially infinite-dimensional random objects, such as dynamic functional data, which are naturally…
Continuous-Time Learning of Probability Distributions: A Case Study in a Digital Trial of Young Children with Type 1 Diabetes
Antonio Álvarez-López, Marcos Matabuena
Understanding how biomarker distributions evolve over time is a central challenge in digital health and chronic disease monitoring. In diabetes, changes in the distribution of gluc…
Perceptrons and localization of attention's mean-field landscape
Antonio Álvarez-López, Borjan Geshkovski, Domènec Ruiz-Balet
The forward pass of a Transformer can be seen as an interacting particle system on the unit sphere: time plays the role of layers, particles that of token embeddings, and the unit…
Convergence, design and training of continuous-time dropout as a random batch method
Antonio Álvarez-López, Martín Hernández
We study continuous-time dropout in controlled differential equations. We introduce a random-batch approximation of additive vector fields. On each time interval of length , a r…
Continuous Temporal Learning of Probability Distributions via Neural ODEs with Applications in Continuous Glucose Monitoring Data
Antonio Álvarez-López, Marcos Matabuena
Modeling the dynamics of probability distributions from time-dependent data samples is a fundamental problem in many fields, including digital health. The goal is to analyze how th…
Cluster-based classification with neural ODEs via control
Antonio Álvarez-López, Rafael Orive-Illera, Enrique Zuazua
We address binary classification using neural ordinary differential equations from the perspective of simultaneous control of data points. We consider a single-neuron architect…