17 citations · 49 across the 10 of their papers we have counts for
13 papers
Coachable agents for interactive gameplay
Roberto Capobianco, Harm van Seijen, Nolan D. Bard +38
Reinforcement learning has proven to be a valuable tool in the creation of advanced AI and robotic systems, contributing to everything from game playing to robotics to foundation m…
Semi-Supervised GCN for learning Molecular Structure-Activity Relationships
Alessio Ragno, Dylan Savoia, Roberto Capobianco
Since the introduction of artificial intelligence in medicinal chemistry, the necessity has emerged to analyse how molecular property variation is modulated by either single atoms…
Molecule Generation from Input-Attributions over Graph Convolutional Networks
Dylan Savoia, Alessio Ragno, Roberto Capobianco
It is well known that Drug Design is often a costly process both in terms of time and economic effort. While good Quantitative Structure-Activity Relationship models (QSAR) can hel…
Detection Accuracy for Evaluating Compositional Explanations of Units
Sayo M. Makinwa, Biagio La Rosa, Roberto Capobianco
The recent success of deep learning models in solving complex problems and in different domains has increased interest in understanding what they learn. Therefore, different approa…
Memory Wrap: a Data-Efficient and Interpretable Extension to Image Classification Models
Biagio La Rosa, Roberto Capobianco, Daniele Nardi
Due to their black-box and data-hungry nature, deep learning techniques are not yet widely adopted for real-world applications in critical domains, like healthcare and justice. Thi…
Reinforcement Learning for Optimization of COVID-19 Mitigation policies
Varun Kompella, Roberto Capobianco, Stacy Jong +5
The year 2020 has seen the COVID-19 virus lead to one of the worst global pandemics in history. As a result, governments around the world are faced with the challenge of protecting…