Abstract: The Particle and Astrophysical Science Computing Center (PIC) is a multifaceted data centre located adjacent to the Computer Vision Center (CVC). In this presentation, we outline various projects within PIC, including its role as a high-throughput facility supporting experiments such as the Euclid satellite, Large Hadron Collider (LHC) experiments, magic telescopes, and the Cherenkov … Read more
Abstract: In this seminar, we will first cover irresponsible AI: (1) discrimination (e.g., facial recognition, justice); (2) phrenology (e.g., biometric-based predictions); (3) limitations (e.g., human incompetence, minimal adversarial AI), (4) indiscriminate use of computing resources (e.g., large language models) and (5) the impact of generative AI (disinformation, mental health and copyright issues). These examples do … Read more
Abstract: In this seminar, Dr. Silvana Silva will present her research during the past years within the field of neuroscience, which has focused on data modeling and analysis using brain images obtained with EEG, MEG, and fMRI. First, a network-theoretical analysis of MEG, where sensors are identified with nodes and the interaction between channel time-series … Read more
Abstract: While artificial intelligence is making ever-larger strides, we cannot neglect the potential for its impact on the way we nurture human intelligence. Education is without a doubt a primary candidate for a beneficial application of generative AI and machine learning. In this talk, Dr. Elitza Maneva will specifically concentrate on their application to the … Read more
Abstract: In this seminar, the research conducted over the past years will be presented, along with new projects or ideas to be implemented in the future. The objective is to share prior experiences and promote synergies with other researchers and groups within the Computer Vision Center. Firstly, we will briefly discuss the research conducted during … Read more
Abstract: Curiosity, the intrinsic desire to know and explore, is a fundamental drive in human behavior with far-reaching implications. It serves as a catalyst for cognitive improvement, enriching internal models of the world and fostering non-instrumental information seeking. Recent studies highlight the neural underpinnings of curiosity, revealing activation of reward-related mesolimbic dopaminergic pathways, with the … Read more
Abstract: Due to the profundity of the concept of artistic style the optimal solution for style transfer is ill-defined. The variety of approaches that have been proposed represent partial solutions to varying degrees of efficiency, usability and quality of results. In this work a photo-realistic style transfer method for image and video based on vision … Read more
Abstract: A calibrated machine learning model produces probabilistic predictions that are well-aligned with real probabilities: it tends to be more certain when it is correct. Unfortunately, the unique characteristics of modern neural networks, e.g. over-parametrization or iterative training dynamics, can often result in overfitting the training data and generating over-confident predictions. The goal of this … Read more
We are pleased to present the Quantum Machine Learning Group (QML-CVC) on Friday, October 20, 2023. We will introduce the people and the main lines of work of the QML-CVC Group, discussing fundamental components and scientific challenges of the Quantum Machine Learning field while identifying potential applications in Computer Vision. The event will start with … Read more
Abstract: While machine learning models are continually improving, for most tasks they fail to achieve perfect predictive performance. In order to be a valuable tool in decision-making under uncertainty, it stands to reason that we want some statistical guarantees on the quality of probabilistic predictive models. Research into calibration regained popularity after repeated empirical observations … Read more
