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Mostrati risultati da 1 a 20 di 35
Tipologia Anno Titolo Titolo inglese Autore File
Lauree magistrali 2025 A data-driven controllability analysis of cortico-cortical evoked potentials A data-driven controllability analysis of cortico-cortical evoked potentials YAVAS, MIHRIBAN
Lauree magistrali 2023 A Machine Learning Approach to Estimate Stray Losses in Power Transformers A Machine Learning Approach to Estimate Stray Losses in Power Transformers RODRIGUES VERO FILHO, EMERSON
Lauree magistrali 2024 A simple algorithm for uncertainty quantification in Snake A simple algorithm for uncertainty quantification in Snake GIORGETTI, LUCA
Lauree triennali 2022 Attrattori dinamici nelle reti neurali ricorrenti Attractors of recurrent neural networks BELTRAME, GINEVRA
Lauree magistrali 2023 Audio Signal Analysis using Deep Learning Audio Signal Analysis using Deep Learning HOETH, MAX HENNING
Lauree magistrali 2023 Closed-loop neurostimulation via reservoir computing Closed-loop neurostimulation via reservoir computing MAZZOCCHETTI, LUCA
Lauree triennali 2023 Confronto di reti neurali ricorrenti addestrate con algoritmi standard e biologicamente plausibili Comparison of recurrent neural networks trained with standard and biologically plausible learning algorithms BORTOLATO, ANGELA
Lauree triennali 2022 Connettività dinamica e non-linearità in un modello computazionale del cervello Dynamical connectivity and nonlinearity in a whole-brain computational model CERNI, PAOLO LAPO
Lauree triennali 2022 Connettività dinamica in un modello computazionale del cervello affetto da ictus Dynamical connectivity in a whole-brain computational model of stroke COLLICELLI, SILVIA
Lauree magistrali 2024 Deep learning approaches for preprocessing and analysis of neuroimaging data Deep learning approaches for preprocessing and analysis of neuroimaging data WATHTHE LIYANAGE, WAGEESHA WIDURANGA
Lauree magistrali 2023 Development and calibration of a predictive physics-based model for solar array power degradation in spacecraft Development and calibration of a predictive physics-based model for solar array power degradation in spacecraft SGORLON GAIATTO, CARLO
Lauree triennali 2025 Dimensionalità dell'attività in reti neurali Dimensionality of activity in neural networks RUOTOLO, ALESSANDRO
Lauree magistrali 2025 Efficient emulation of reaction-diffusion systems using SciML Efficient emulation of reaction-diffusion systems using SciML POCCIANTI, GABRIELE
Lauree magistrali 2025 End-to-End Development of an AI-Driven Clinical Documentation and Data Processing Platform End-to-End Development of an AI-Driven Clinical Documentation and Data Processing Platform AVILES MORENO, MIGUEL
Lauree magistrali 2023 Incorporating Machine Learning for Value-Based Pricing: An Innovative Framework Combining Quotation and Sales Analytics Incorporating Machine Learning for Value-Based Pricing: An Innovative Framework Combining Quotation and Sales Analytics CAPODAGLIO, ALESSANDRO MARIA
Lauree magistrali 2023 Information Theoretic Analysis of Deep Neural Networks Information Theoretic Analysis of Deep Neural Networks BERGAMIN, ELEONORA
Lauree magistrali 2024 Latent space modelling of whole-brain dynamics: a Koopman-theoretical approach Latent space modelling of whole-brain dynamics: a Koopman-theoretical approach TANCREDI, RICCARDO
Lauree triennali 2024 Linearizzazione e predizione con reti neurali ricorrenti Linearizing and forecasting with recurrent neural networks DE POLI, NICCOLÒ
Lauree magistrali 2025 Modeling brain dynamics through recurrent neural networks: a linearization approach Modeling brain dynamics through recurrent neural networks: a linearization approach ELSA SANJAI, SANDRA
Lauree magistrali 2025 Modeling the weather's influence on air and water quality This thesis project aims at studying the complex relation between air quality, water quality, and the weather. We will analyze data on air quality index (AQI) and water quality/quantity, obtained by probes placed outdoors and in the sewages. The first step will be to obtain a proper data set for analysis, integrating several measurements from the pre-existing ARPA database. The second step will consist of using machine-learning and other techniques for the analysis of complex multivariate time series to obtain a model of the joint time evolution of water and air quality, and their modulation by key meteorological parameters (such as rainfall, temperature, and humidity), considered as external forcing factors. Finally, we will assess the model's performance in forecasting. CHATURVEDI, PANKHURI
Mostrati risultati da 1 a 20 di 35
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