22 citations · 60 across the 10 of their papers we have counts for
12 papers
ALICE: In-context, Zero-shot, Mutual Information Estimation
Giulio Franzese, Simone Rossi, Pietro Michiardi
Estimating mutual information (MI) from samples is a central objective in a variety of scientific fields. Modern neural estimators are accurate in the large-data regime, but they f…
DrivingVoxels: Compositional Sparse Voxel Rasterization for Dynamic Driving Scene Reconstruction
Tania Aguirre, Luis Roldão, Moussab Bennehar +4
Reconstructing dynamic urban scenes remains challenging due to the unbounded nature of driving environments and the presence of multiple dynamic objects. Currently, potentially fas…
A Bayesian Perspective on the Role of Epistemic Uncertainty for Delayed Generalization in In-Context Learning
Abdessamed Qchohi, Simone Rossi
In-context learning enables transformers to adapt to new tasks from a few examples at inference time, while grokking highlights that this generalization can emerge abruptly only af…
Scaling Laws for Uncertainty in Deep Learning
Mattia Rosso, Simone Rossi, Giulio Franzese +2
Deep learning has recently revealed the existence of scaling laws, demonstrating that model performance follows predictable trends based on dataset and model sizes. Inspired by the…
Continuous-Time Functional Diffusion Processes
Giulio Franzese, Giulio Corallo, Simone Rossi +3
We introduce Functional Diffusion Processes (FDPs), which generalize score-based diffusion models to infinite-dimensional function spaces. FDPs require a new mathematical framework…
How Much is Enough? A Study on Diffusion Times in Score-based Generative Models
Giulio Franzese, Simone Rossi, Lixuan Yang +4
Score-based diffusion models are a class of generative models whose dynamics is described by stochastic differential equations that map noise into data. While recent works have sta…