In this talk, I will describe the main techniques of photographic 3D-reconstruction, which are structure-from-motion, multi-view stereoscopy, shape-from-shading and photometric stereo. I will highligh...
Motivated by the study of smoothings of rational surface singularities as well as symplectic fillings of plumbed 3-manifolds, we consider an analogue problem in a purely topological setting. The quest...
In this talk I will present how proteomic, nuclear medicine and imaging data can be used to model the patho-physiology of cancer at different scales, from single cell, through tissues to organs. The m...
Stochastic optimization algorithms are widely employed for problems arising in machine learning but significant issues in their use are open. In fact, tuning these algorithms for each application may ...
Optimal control and Reinforcement Learning (RL) deal both with sequential decision-making problems, although they use different tools. We have investigated the connection between these two research ar...
We consider some problems concerning the geometry of the Chern connection, including: metrics with constant Chern-scalar curvature; the generalizations of the Kähler-Einstein condition to the non-Kähl...
Although traffic models have been extensively studied, obtaining trustful forecast from these models is still challenging, since the evolution of traffic is also exposed to the presence of uncertainti...
Semi-lagrangian schemes for discretization of the dynamic programming principle are based on a time discretization projected on a state-space grid. The use of a structured grid makes this approach not...
For evident reasons, Cancer Biology is one of the most challenging topics of current medical research and understanding the mechanism behind its uncontrolled growth is a crucial issue. Among other exp...
