101 citations · 249 across the 7 of their papers we have counts for
8 papers
A Feature Reuse Framework with Texture-adaptive Aggregation for Reference-based Super-Resolution
Xiaoyong Mei, Yi Yang, Ming Li +3
Reference-based super-resolution (RefSR) has gained considerable success in the field of super-resolution with the addition of high-resolution reference images to reconstruct low-r…
Structure-based Drug Design with Equivariant Diffusion Models
Arne Schneuing, Charles Harris, Yuanqi Du +10
Structure-based drug design (SBDD) aims to design small-molecule ligands that bind with high affinity and specificity to pre-determined protein targets. Generative SBDD methods lev…
Approximate Latent Force Model Inference
Jacob D. Moss, Felix L. Opolka, Bianca Dumitrascu +1
Physically-inspired latent force models offer an interpretable alternative to purely data driven tools for inference in dynamical systems. They carry the structure of differential…
Logic Explained Networks
Gabriele Ciravegna, Pietro Barbiero, Francesco Giannini +4
The large and still increasing popularity of deep learning clashes with a major limit of neural network architectures, that consists in their lack of capability in providing human-…
Entropy-based Logic Explanations of Neural Networks
Pietro Barbiero, Gabriele Ciravegna, Francesco Giannini +3
Explainable artificial intelligence has rapidly emerged since lawmakers have started requiring interpretable models for safety-critical domains. Concept-based neural networks have…
Graph representation forecasting of patient's medical conditions: towards a digital twin
Pietro Barbiero, Ramon Viñas Torné, Pietro Lió
Objective: Modern medicine needs to shift from a wait and react, curative discipline to a preventative, interdisciplinary science aiming at providing personalised, systemic and pre…
The Computational Patient has Diabetes and a COVID
Pietro Barbiero, Pietro Lió
Medicine is moving from a curative discipline to a preventative discipline relying on personalised and precise treatment plans. The complex and multi level pathophysiological patte…
Modelling the order of driver mutations and metabolic mutations as structures in cancer dynamics
Gianluca Ascolani, Pietro Lió
Recent works have stressed the important role that random mutations have in the development of cancer phenotype. We challenge this current view by means of bioinformatic data analy…