Davide Evangelista

35 papers A* 1Journal 29Unranked 4
YearRankTypeTitle / Venue / Authors
2026 J jnl
A Diffusion-Based Generative Prior Approach to Sparse-view Computed Tomography.
CoRR
Davide Evangelista, Pasquale Cascarano, Elena Loli Piccolomini
2026 J jnl
Adaptive Weighted Total Variation Boosted by Learning Techniques in Few-View Tomographic Imaging.
J. Sci. Comput.
Elena Morotti, Davide Evangelista, Andrea Sebastiani, Elena Loli Piccolomini
2026 J jnl
CLeAN: Continual Learning Adaptive Normalization in Dynamic Environments.
CoRR
Isabella Marasco, Davide Evangelista, Elena Loli Piccolomini, Michele Colajanni
2026 J jnl
Controlling ensemble variance in diffusion models: an application for reanalyses downscaling.
Neural Comput. Appl.
Fabio Merizzi, Davide Evangelista, Harilaos Loukos
2026 J jnl
The CompMath-MCQ Dataset: Are LLMs Ready for Higher-Level Math?
CoRR
Bianca Raimondi, Francesco Pivi, Davide Evangelista, Maurizio Gabbrielli
2025 J jnl
A Data-Dependent Regularization Method Based on the Graph Laplacian.
SIAM J. Sci. Comput.
Davide Bianchi, Davide Evangelista, Stefano Aleotti, Marco Donatelli, Elena Loli Piccolomini, Wenbin Li
2025 J jnl
Adaptive Weighted Total Variation boosted by learning techniques in few-view tomographic imaging.
CoRR
Elena Morotti, Davide Evangelista, Andrea Sebastiani, Elena Loli Piccolomini
2025 J jnl
Controlling Ensemble Variance in Diffusion Models: An Application for Reanalyses Downscaling.
CoRR
Fabio Merizzi, Davide Evangelista, Harilaos Loukos
2025 J jnl
Deep Guess acceleration for explainable image reconstruction in sparse-view CT.
Comput. Medical Imaging Graph.
Elena Loli Piccolomini, Davide Evangelista, Elena Morotti
2025 — conf
LIP-CAR: A Learned Inverse Problem Approach for Medical Imaging with Contrast Agent Reduction.
MICCAI (11)
Davide Evangelista, Elena Morotti, Sonia Colombo Serra, Pengpeng Luo, Giovanni Valbusa, Davide Bianchi
2025 A* conf
Language Models Are Implicitly Continuous.
ICLR
Samuele Marro, Davide Evangelista, X. Angelo Huang, Emanuele La Malfa, Michele Lombardi, Michael J. Wooldridge
2025 J jnl
Language Models Are Implicitly Continuous.
CoRR
Samuele Marro, Davide Evangelista, X. Angelo Huang, Emanuele La Malfa, Michele Lombardi, Michael J. Wooldridge
2025 J jnl
Neural network-based inversion of NMR dispersion profiles for enhanced analysis of food systems.
Neural Comput. Appl.
Giovanni Vito Spinelli, Davide Evangelista, Liwei Hu, Fabiana Zama
2025 J jnl
On the flow matching interpretability.
CoRR
Francesco Pivi, Simone Gazza, Davide Evangelista, Roberto Amadini, Maurizio Gabbrielli
2025 J jnl
To Be or Not to Be Stable, That Is the Question: Understanding Neural Networks for Inverse Problems.
SIAM J. Sci. Comput.
Davide Evangelista, Elena Loli Piccolomini, Elena Morotti, James G. Nagy
2024 J jnl
Deep Guess acceleration for explainable image reconstruction in sparse-view CT.
CoRR
Elena Loli Piccolomini, Davide Evangelista, Elena Morotti
2024 J jnl
Inpainting with style: forcing style coherence to image inpainting with deep image prior.
Frontiers Comput. Sci.
Elena Morotti, Fabio Merizzi, Davide Evangelista, Pasquale Cascarano
2024 J jnl
LIP-CAR: contrast agent reduction by a deep learned inverse problem.
CoRR
Davide Bianchi, Sonia Colombo Serra, Davide Evangelista, Pengpeng Luo, Elena Morotti, Giovanni Valbusa
2024 — —
Regularization meets GreenAI: a new framework for image reconstruction in life sciences applications.
Davide Evangelista
2024 J jnl
Space-Variant Total Variation boosted by learning techniques in few-view tomographic imaging.
CoRR
Elena Morotti, Davide Evangelista, Andrea Sebastiani, Elena Loli Piccolomini
2023 J jnl
A data-dependent regularization method based on the graph Laplacian.
CoRR
Davide Bianchi, Davide Evangelista, Stefano Aleotti, Marco Donatelli, Elena Loli Piccolomini, Wenbin Li
2023 J jnl
Ambiguity in Solving Imaging Inverse Problems with Deep-Learning-Based Operators.
J. Imaging
Davide Evangelista, Elena Morotti, Elena Loli Piccolomini, James G. Nagy
2023 J jnl
Ambiguity in solving imaging inverse problems with deep learning based operators.
CoRR
Davide Evangelista, Elena Morotti, Elena Loli Piccolomini, James G. Nagy
2023 — conf
Graph Laplacian and Neural Networks for Inverse Problems in Imaging: GraphLaNet.
SSVM
Davide Bianchi, Marco Donatelli, Davide Evangelista, Wenbin Li, Elena Loli Piccolomini
2023 J jnl
Image Embedding for Denoising Generative Models.
CoRR
Andrea Asperti, Davide Evangelista, Samuele Marro, Fabio Merizzi
2023 J jnl
Image embedding for denoising generative models.
Artif. Intell. Rev.
Andrea Asperti, Davide Evangelista, Samuele Marro, Fabio Merizzi
2023 J jnl
RISING: A new framework for model-based few-view CT image reconstruction with deep learning.
Comput. Medical Imaging Graph.
Davide Evangelista, Elena Morotti, Elena Loli Piccolomini
2023 — conf
Robust Non-convex Model-Based Approach for Deep Learning-Based Image Processing.
NUMTA (1)
Elena Morotti, Davide Evangelista, Elena Loli Piccolomini
2022 J jnl
RISING a new framework for few-view tomographic image reconstruction with deep learning.
CoRR
Davide Evangelista, Elena Morotti, Elena Loli Piccolomini
2022 J jnl
To be or not to be stable, that is the question: understanding neural networks for inverse problems.
CoRR
Davide Evangelista, James G. Nagy, Elena Morotti, Elena Loli Piccolomini
2021 J jnl
A Green Prospective for Learned Post-Processing in Sparse-View Tomographic Reconstruction.
J. Imaging
Elena Morotti, Davide Evangelista, Elena Loli Piccolomini
2021 J jnl
A Survey on Variational Autoencoders from a Green AI Perspective.
SN Comput. Sci.
Andrea Asperti, Davide Evangelista, Elena Loli Piccolomini
2021 J jnl
A survey on Variational Autoencoders from a GreenAI perspective.
CoRR
Andrea Asperti, Davide Evangelista, Elena Loli Piccolomini
2021 — conf
Dissecting FLOPs Along Input Dimensions for GreenAI Cost Estimations.
LOD
Andrea Asperti, Davide Evangelista, Moreno Marzolla
2021 J jnl
Dissecting FLOPs along input dimensions for GreenAI cost estimations.
CoRR
Andrea Asperti, Davide Evangelista, Moreno Marzolla