Speaker: Sara Barahona Quirós. Abstract: Explainable Machine Learning (XAI) refers to the development of machine learning models and algorithms that not only make accurate decisions but also provide understandable and interpretable explanations for those predictions. In traditional machine learning, particularly… Read More
Generative Artificial Intelligence: A Global Overview
Speaker: Diego de Benito Gorrón. Abstract: Generative Artificial Intelligence (GenAI) has made a strong impact on the technological landscape, redefining paradigms and possibilities. This talk offers a panoramic view of GenAI, with a specific focus on Large Language Models (LLMs)… Read More
Robust Wake-up Word by Two-stage Multi-resolution Ensembles
Speaker: William Fernando López Gaviánez. Abstract: Voice-based interfaces rely on a wake-up word mechanism to initiate communication with devices. However, achieving a robust, energy-efficient, and fast detection remains a challenge. This paper addresses these real production needs by enhancing data… Read More
Towards automatic inspection of nuclear fuel elements in spent fuel storage with AI tools.
Speaker: Sergio Segovia González. Abstract: New way to automatize the inspection of nuclear fuel elements in spent fuel storage processing video signal and audio signal. For video signal, it is developed a custom database including images from several nuclear facilities… Read More
FLIP (Fitness Landscape Inference for Proteins)
Speaker: Natalia Pinto Estéban. Abstract: Machine learning is growing in significance across various research domains. One of these domains is biology, specifically focusing on protein engineering and directed evolution techniques. This presentation is grounded in the FLIP paper (Fitness Landscape… Read More
Knowledge Distillation to Compress and Accelerate Large Models
Speaker: Laura Herrera Alarcón. Abstract: These papers present the idea of Knowledge Distillation, a method to compress and accelerate large models with high computational and storage cost. Thanks to this, these models can be used for real-time applications or in… Read More
An introduction to Spiking Neural Networks (SNNs) and neuromorphic computing
Speaker: Doroteo Torre Toledano. Abstract: This talk is an overview of Spiking Neural Networks, a biologically inspired type of neural networks that outputs digital spikes over continuous time in an asynchronous way, instead of continuous values at frame-by-frame synchronous times… Read More
A Systematic Study on the Use of the Log-Likelihood Ratio Cost in Forensic Science
Speaker: Daniel Ramos Castro. Abstract: It is increasingly common in forensic science to report evidential findings in terms of a likelihood ratio (LR). Such analyses are often supported by (semi-)automated LR systems based on statistical methods, which allows for validation… Read More
Language Models in Protein Engineering
Speaker: Joaquín González Rodríguez. Abstract: The sequences of aminoacids describing a protein can be efficiently handled by language models. In this talk, present and future applications of Transformer-based protein Language Models are surveyed, focusing in databases, benchmarks and models already… Read More
Automatic Wheeze Segmentation Using Harmonic-Percussive Source Separation and Empirical Mode Decomposition
Speaker: Miguel Ángel Martínez Pay. Abstract: Based on https://ieeexplore.ieee.org/document/10051156. Wheezes, a respiratory anomaly in patients with respiratory conditions, are significant for clinical assessment, particularly in gauging bronchial obstruction. While conventional auscultation is the norm for wheeze analysis, recent years emphasize… Read More