Image de couverture de livre

Multimodal and multicontrast image fusion via deep generative models

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Dimitri, Giovanna Maria, Spasov, Simeon, Duggento, Andrea, Passamonti, Luca, Li`o, Pietro, Toschi, Nicola
Format:	Preprint
Publié:	2023
Sujets:	Machine Learning
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Transforming Multimodal Models into Action Models for Radiotherapy
par: Ferrante, Matteo, et autres
Publié: (2025)

Integrating Background Knowledge in Medical Semantic Segmentation with Logic Tensor Networks
par: Bergamin, Luca, et autres
Publié: (2025)

Toward Explainable Offline RL: Analyzing Representations in Intrinsically Motivated Decision Transformers
par: Guiducci, Leonardo, et autres
Publié: (2025)

Multimodal signal fusion for stress detection using deep neural networks: a novel approach for converting 1D signals to unified 2D images
par: Hasanpoor, Yasin, et autres
Publié: (2025)

Training Neural Networks by Optimizing Neuron Positions
par: Erb, Laura, et autres
Publié: (2025)

Hyperbolic Graph Neural Networks Under the Microscope: The Role of Geometry-Task Alignment
par: Naddeo, Dionisia, et autres
Publié: (2026)

Quantum latent distributions in deep generative models
par: Bacarreza, Omar, et autres
Publié: (2025)

Boosting Team Modeling through Tempo-Relational Representation Learning
par: De Luca, Vincenzo Marco, et autres
Publié: (2025)

A multi-head deep fusion model for recognition of cattle foraging events using sound and movement signals
par: Ferrero, Mariano, et autres
Publié: (2025)

The statistical thermodynamics of generative diffusion models: Phase transitions, symmetry breaking and critical instability
par: Ambrogioni, Luca
Publié: (2023)

Actionable Real-Time Modeling of Surgical Team Dynamics via Time-Expanded Interaction Graphs
par: De Luca, Vincenzo Marco, et autres
Publié: (2026)

Discovering interpretable models of scientific image data with deep learning
par: Soelistyo, Christopher J., et autres
Publié: (2024)

Bridging Auditory Perception and Language Comprehension through MEG-Driven Encoding Models
par: Ciferri, Matteo, et autres
Publié: (2024)

Quasi Monte Carlo methods enable extremely low-dimensional deep generative models
par: Martinez, Miles, et autres
Publié: (2026)

Spectral entropy prior-guided deep feature fusion architecture for magnetic core loss
par: Yao, Cong, et autres
Publié: (2025)

Piecewise deterministic generative models
par: Bertazzi, Andrea, et autres
Publié: (2024)

Active inference and deep generative modeling for cognitive ultrasound
par: van Sloun, Ruud JG
Publié: (2024)

Knowledge-data fusion oriented traffic state estimation: A stochastic physics-informed deep learning approach
par: Wang, Ting, et autres
Publié: (2024)

Multimodal learning of melt pool dynamics in laser powder bed fusion
par: Mojumder, Satyajit, et autres
Publié: (2025)

A novel data generation scheme for surrogate modelling with deep operator networks
par: Choubey, Shivam, et autres
Publié: (2024)

Schrödinger bridge based deep conditional generative learning
par: Huang, Hanwen
Publié: (2024)

Enhancing SRTM digital elevation models with deep-learning-based super-resolution image generation
par: Leonardo Assumpção Moreira
Publié: (2022)

Nonparametric Instrumental Regression via Kernel Methods is Minimax Optimal
par: Meunier, Dimitri, et autres
Publié: (2024)

Coupled generator decomposition for fusion of electro- and magnetoencephalography data
par: Olsen, Anders Stevnhoved, et autres
Publié: (2024)

From Bytes to Bites: Using Country Specific Machine Learning Models to Predict Famine
par: Kapoor, Salloni, et autres
Publié: (2024)

If Concept Bottlenecks are the Question, are Foundation Models the Answer?
par: Debole, Nicola, et autres
Publié: (2025)

Learning mental states estimation through self-observation: a developmental synergy between intentions and beliefs representations in a deep-learning model of Theory of Mind
par: Bianco, Francesca, et autres
Publié: (2024)

Disentangling representations of retinal images with generative models
par: Müller, Sarah, et autres
Publié: (2024)

Evaluating Angle and Amplitude Encoding Strategies for Variational Quantum Machine Learning: their impact on model's accuracy
par: Tudisco, Antonio, et autres
Publié: (2025)

Importance of realism in procedurally-generated synthetic images for deep learning: case studies in maize and canola
par: Khan, Nazifa Azam, et autres
Publié: (2024)

Scalable physics-informed deep generative model for solving forward and inverse stochastic differential equations
par: Zhou, Shaoqian, et autres
Publié: (2025)

Generating Graphs via Spectral Diffusion
par: Minello, Giorgia, et autres
Publié: (2024)

Toward cross-subject and cross-session generalization in EEG-based emotion recognition: Systematic review, taxonomy, and methods
par: Apicella, Andrea, et autres
Publié: (2022)

DEQuify your force field: More efficient simulations using deep equilibrium models
par: Burger, Andreas, et autres
Publié: (2025)

Stochastic forest transition model dynamics and parameter estimation via deep learning
par: Kumabe, Satoshi, et autres
Publié: (2025)

Outsourced diffusion sampling: Efficient posterior inference in latent spaces of generative models
par: Venkatraman, Siddarth, et autres
Publié: (2025)

Attribution assignment for deep-generative sequence models enables interpretability analysis using positive-only data
par: Frank, Robert, et autres
Publié: (2025)

xAI-Drop: Don't Use What You Cannot Explain
par: De Luca, Vincenzo Marco, et autres
Publié: (2024)

Inversion dynamics of class manifolds in deep learning reveals tradeoffs underlying generalisation
par: Ciceri, Simone, et autres
Publié: (2023)

Evaluating deep learning models for fault diagnosis of a rotating machinery with epistemic and aleatoric uncertainty
par: Jalayer, Reza, et autres
Publié: (2024)