EVANGELISTA, DAVIDE
EVANGELISTA, DAVIDE
DISI - DIPARTIMENTO DI INFORMATICA - SCIENZA E INGEGNERIA
Ricercatori a tempo determinato
A Data-Dependent Regularization Method Based on the Graph Laplacian
2025 Bianchi, Davide; Evangelista, Davide; Aleotti, Stefano; Donatelli, Marco; Piccolomini, Elena Loli; Li, Wenbin
Deep Guess acceleration for explainable image reconstruction in sparse-view CT
2025 Loli Piccolomini, Elena; Evangelista, Davide; Morotti, Elena
Robust Non-convex Model-Based Approach for Deep Learning-Based Image Processing
2025 Morotti, Elena; Evangelista, Davide; Loli Piccolomini, Elena
TO BE OR NOT TO BE STABLE, THAT IS THE QUESTION: UNDERSTANDING NEURAL NETWORKS FOR INVERSE PROBLEMS
2025 Evangelista, D.; Piccolomini, E. L.; Morotti, E.; Nagy, J. G.
Enhancing Food Quality Analysis: Deep Neural Network Inversion of NMRD Profiles with Quadrupolar Dips
2024 Davide Evangelista, Liwei Hu, Giovanni V. Spinelli, Fabiana Zama
Enhancing NMR Analysis: Deep Neural Network Inversion of NMRD Profiles with Quadrupolar Dips
2024 Spinelli, GIOVANNI VITO; Zama, Fabiana; Evangelista, Davide; Hu, Liwei
Inpainting with style: forcing style coherence to image inpainting with deep image prior
2024 Morotti, Elena; Merizzi, Fabio; Evangelista, Davide; Cascarano, Pasquale
Neural network-based inversion of NMR dispersion profiles for enhanced analysis of food systems
2024 Spinelli, Giovanni Vito; Evangelista, Davide; Hu, Liwei; Zama, Fabiana
Ambiguity in Solving Imaging Inverse Problems with Deep-Learning-Based Operators
2023 Evangelista D.; Morotti E.; Piccolomini E.L.; Nagy J.
Graph Laplacian and Neural Networks for Inverse Problems in Imaging: GraphLaNet
2023 Bianchi, D.; Donatelli, M.; Evangelista, D.; Li, W.; Piccolomini, E. L.
Image embedding for denoising generative models
2023 Asperti, Andrea; Evangelista, Davide; Marro, Samuele; Merizzi, Fabio
RISING: A new framework for model-based few-view CT image reconstruction with deep learning
2023 Evangelista, D.; Morotti, E.; Loli Piccolomini, E.
Dissecting FLOPs Along Input Dimensions for GreenAI Cost Estimations
2022 Asperti, Andrea; Evangelista, Davide; Marzolla, Moreno
A green prospective for learned post-processing in sparse-view tomographic reconstruction
2021 Morotti E.; Evangelista D.; Loli Piccolomini E.
A Survey on Variational Autoencoders from a Green AI Perspective
2021 Asperti, Andrea; Evangelista, Davide; Loli Piccolomini, Elena
| Titolo | Autore(i) | Anno | Periodico | Editore | Tipo | File |
|---|---|---|---|---|---|---|
| A Data-Dependent Regularization Method Based on the Graph Laplacian | Bianchi, Davide; Evangelista, Davide; Aleotti, Stefano; Donatelli, Marco; Piccolomini, Elena Loli...; Li, Wenbin | 2025-01-01 | SIAM JOURNAL ON SCIENTIFIC COMPUTING | - | 1.01 Articolo in rivista | - |
| Deep Guess acceleration for explainable image reconstruction in sparse-view CT | Loli Piccolomini, Elena; Evangelista, Davide; Morotti, Elena | 2025-01-01 | COMPUTERIZED MEDICAL IMAGING AND GRAPHICS | - | 1.01 Articolo in rivista | - |
| Robust Non-convex Model-Based Approach for Deep Learning-Based Image Processing | Morotti, Elena; Evangelista, Davide; Loli Piccolomini, Elena | 2025-01-01 | - | Springer Nature Switzerland | 2.01 Capitolo / saggio in libro | - |
| TO BE OR NOT TO BE STABLE, THAT IS THE QUESTION: UNDERSTANDING NEURAL NETWORKS FOR INVERSE PROBLEMS | Evangelista, D.; Piccolomini, E. L.; Morotti, E.; Nagy, J. G. | 2025-01-01 | SIAM JOURNAL ON SCIENTIFIC COMPUTING | - | 1.01 Articolo in rivista | - |
| Enhancing Food Quality Analysis: Deep Neural Network Inversion of NMRD Profiles with Quadrupolar Dips | Davide Evangelista, Liwei Hu, Giovanni V. Spinelli, Fabiana Zama | 2024-01-01 | - | - | 4.03 Poster | - |
| Enhancing NMR Analysis: Deep Neural Network Inversion of NMRD Profiles with Quadrupolar Dips | Spinelli, GIOVANNI VITO; Zama, Fabiana; Evangelista, Davide; Hu, Liwei | 2024-01-01 | - | - | 4.02 Riassunto (Abstract) | - |
| Inpainting with style: forcing style coherence to image inpainting with deep image prior | Morotti, Elena; Merizzi, Fabio; Evangelista, Davide; Cascarano, Pasquale | 2024-01-01 | FRONTIERS IN COMPUTER SCIENCE | - | 1.01 Articolo in rivista | fcomp-06-1478233 (1).pdf |
| Neural network-based inversion of NMR dispersion profiles for enhanced analysis of food systems | Spinelli, Giovanni Vito; Evangelista, Davide; Hu, Liwei; Zama, Fabiana | 2024-01-01 | NEURAL COMPUTING & APPLICATIONS | - | 1.01 Articolo in rivista | NMR_net_springer.pdf |
| Ambiguity in Solving Imaging Inverse Problems with Deep-Learning-Based Operators | Evangelista D.; Morotti E.; Piccolomini E.L.; Nagy J. | 2023-01-01 | JOURNAL OF IMAGING | - | 1.01 Articolo in rivista | jimaging23.pdf |
| Graph Laplacian and Neural Networks for Inverse Problems in Imaging: GraphLaNet | Bianchi, D.; Donatelli, M.; Evangelista, D.; Li, W.; Piccolomini, E. L. | 2023-01-01 | - | - | 4.01 Contributo in Atti di convegno | - |
| Image embedding for denoising generative models | Asperti, Andrea; Evangelista, Davide; Marro, Samuele; Merizzi, Fabio | 2023-01-01 | ARTIFICIAL INTELLIGENCE REVIEW | - | 1.01 Articolo in rivista | s10462-023-10504-5.pdf |
| RISING: A new framework for model-based few-view CT image reconstruction with deep learning | Evangelista, D.; Morotti, E.; Loli Piccolomini, E. | 2023-01-01 | COMPUTERIZED MEDICAL IMAGING AND GRAPHICS | - | 1.01 Articolo in rivista | main - RISING.pdf |
| Dissecting FLOPs Along Input Dimensions for GreenAI Cost Estimations | Asperti, Andrea; Evangelista, Davide; Marzolla, Moreno | 2022-01-01 | - | Springer | 4.01 Contributo in Atti di convegno | 2107.11949.pdf |
| A green prospective for learned post-processing in sparse-view tomographic reconstruction | Morotti E.; Evangelista D.; Loli Piccolomini E. | 2021-01-01 | JOURNAL OF IMAGING | - | 1.01 Articolo in rivista | jimaging-07-00139-v2.pdf |
| A Survey on Variational Autoencoders from a Green AI Perspective | Asperti, Andrea; Evangelista, Davide; Loli Piccolomini, Elena | 2021-01-01 | SN COMPUTER SCIENCE | - | 1.01 Articolo in rivista | Asperti2021_Article_ASurveyOnVariationalAutoencode.pdf |