Telecomunicaciones, información y comunicación

A Shortcut to Statistically Steady-State Turbulence with Flow Matching

- Many nonlinear physical systems exhibit an initial transient phase in which perturbations grow before nonlinear interactions lead to a statistically steady state. While this saturated regime is of...

The log log jam in Gaussian state tomography

- Unlike in finite dimensions, quantum information in continuous-variable systems has the peculiar feature that without imposing physical constraints, the sample complexity of state tomography can be...

Robustness of Deep Learning Models for PV Power Forecasting under NWP Forecast Errors: A Spatiotemporal and Physically Interpretable Analysis

- Engineering use of AI forecasting models requires not only high nominal accuracy but also predictable behavior under uncertain inputs. In photovoltaic (PV) forecasting, this requirement is especially...

Exact and Calibrated Diffusion Reconstruction for Digital Breast Tomosynthesis

- Limited-angle digital breast tomosynthesis (DBT) reconstructs a volume from a few low-dose projections over a narrow arc. At a representative nine-view, $25^{\circ}$ protocol more than 98% of image...

Real-time fall detection based on vision for low-power edge platforms

- Falling detection is vital for elderly care and intelligent surveillance; however, prevailing vision-based approaches predominantly frame it as static pose classification or discrete temporal pattern...

Accelerated Mixing Time of Randomized Hamiltonian Monte Carlo

- We show the Randomized Hamiltonian Monte Carlo (RHMC) algorithm has accelerated mixing time guarantees for sampling from log-concave probability distributions. RHMC proceeds by repeatedly simulating...

ANGLE: Angular Neural Generative Learning via Engression

- Circular data, representing angles or directions, are frequently encountered in computer vision, biology, geology, and meteorology. Traditional regression targets the conditional mean, which is often...

When Close Enough Is Not Enough: Autoregressive Drift in Quantum Circuit Synthesis

- Quantum circuit optimization for fault-tolerant computing requires exact functional equivalence while minimizing expensive non-Clifford resources such as T gates. We study this problem using a...

Detecting Phishing in Ethereum Networks using Quantum Machine Learning

- This article explores the potential of Quantum Machine Learning (QML), specifically assessing a Quantum Support Vector Machine (QSVM) and a Variational Quantum Classifier (VQC) for detecting...

Learning-enabled Acceleration of Scenario-based Model Predictive Control

- Scenario-based model predictive control (SBMPC) is a variant of model predictive control (MPC) that explicitly accounts for uncertainty by optimizing control actions over multiple predicted...

Physically Consistent Parameter Inference: Transparent Machine Learning Emulation in High Energy Physics and Cosmology

- Global fits in high energy physics and cosmology often face the challenge of exploring high-dimensional parameter spaces with computationally expensive or topologically complex likelihood functions....

Contrasting statistical patterns in melodic and molecular evolution reveal distinctive constraints in a culturally evolving system

- Evolved sequences can be used to infer the rules of evolution. Orally transmitted folk melodies are evolved sequences whose similarity to protein sequences (one-dimensional, drawn from a limited...

Quantum PDE Solvers in Practice: Application-Driven Benchmarking of the Heat Equation

- Quantum PDE solvers are difficult to evaluate in practice because published studies use different discretizations, output models, reconstruction rules, and hardware assumptions. We present a...

Phase Transition of Eigenvalues of Covariances from the Spiked Mixture Model in High-dimensional Regimes

- The spiked mixture model (SMM) has been introduced as a probabilistic model that generalizes the single-spike (Wishart) model to a mixture model form. With applications ranging from imaging mass...

The Limits of Price Discrimination with a Bayesian Seller

- We study the limits of third-degree price discrimination when the production cost is Bayesian and private to the seller, generalizing the seminal work of Bergemann, Brooks and Morris (2015). The...

Improving Autonomous Nano-drones Performance via Automated End-to-End Optimization and Deployment of DNNs

- The evolution of energy-efficient ultra-low-power (ULP) parallel processors and the diffusion of convolutional neural networks (CNNs) are fueling the advent of autonomous driving nano-sized unmanned...

Medical Image Segmentation based on Deep Active Contour and Mean Curvature Loss Function

- Medical image segmentation is a crucial task in the field of clinical analysis and applications. Though deep learning techniques recently play a crucial role in several scenarios, the training at the...

Q2NSViz: An Open-source Standalone Visualizer for Quantum Network Simulations

- The unique and non-classical features of quantum networks make their simulation and intuitive understanding inherently difficult. In this work, we present Q2NSViz, an open-source Python-based...

Partial Identification with Multiple Nonlinear Measurements of a Latent Regressor

- We study linear regression when the regressor is latent and observed only through multiple noisy measurements, each a smooth but possibly nonlinear function of the latent variable. The problem is...

Stability and Bifurcations of Planar Switched Linear and Homogeneous Systems

- We prove new necessary and sufficient conditions for uniform asymptotic stability under arbitrary switching of two-dimensional switched homogeneous systems with a finite number of subsystems using a...

fkcompute: an efficient $F_K$ invariant calculator

- We introduce fkcompute, an open-source package for computing the Gukov--Manolescu invariant of links from a braid presentation. fkcompute implements Park's inverted state sum through a...