14 papers
Constraint-driven Optimization and Parametrization of Industrial NURBS Geometries via Neural Deformation Field
Federico Tamburlin, Giovanni Canali, Giuseppe Alessio D'Inverno +3
This work presents a differentiable framework for the parametrization and shape optimization of industrial CAD geometries represented by multi-patch NURBS surfaces. The method enab…
From Well-Posed Inversion to Learning Design: Physics- Informed Neural Estimation for Autonomic Regulation
Sara Nour Sadoun, Giuseppe Alessio D'Inverno, Francois Cottin +2
Learning-based and physics-informed methods are increasingly used for inverse estimation in controlled nonlinear dynamical systems. However, in many such approaches, the theoretic…
Evaluating passing decision-making in professional football: An enhanced MPNN approach to Receiver Selection
Gabriel Masella, Giuseppe Alessio D'Inverno, Max Goldsmith +1
The process of decision-making in football is characterized by a complex interplay between spatial positioning, opponent pressure, and player intent. This work introduces a Graph N…
On Task Vectors and Gradients
Luca Zhou, Daniele Solombrino, Donato Crisostomi +4
Task arithmetic has emerged as a simple yet powerful technique for model merging, enabling the combination of multiple finetuned models into one. Despite its empirical success, a c…
Revisiting Deep Information Propagation: Fractal Frontier and Finite-size Effects
Giuseppe Alessio D'Inverno, Zhiyuan Hu, Leo Davy +3
Information propagation characterizes how input correlations evolve across layers in deep neural networks. This framework has been well studied using mean-field theory, which assum…
Data-driven multi-agent modelling of calcium interactions in cell culture: PINN vs Regularized Least-squares
Aurora Poggi, Giuseppe Alessio D'Inverno, Hjalmar Brismar +3
Data-driven discovery of dynamics in biological systems allows for better observation and characterization of processes, such as calcium signaling in cell culture. Recent advanceme…