Roberto Capobianco

Orcid: 0000-0002-2219-215X

According to our database1, Roberto Capobianco authored at least 50 papers between 2013 and 2024.

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Bibliography

2024
Prototype-Based Interpretable Graph Neural Networks.
IEEE Trans. Artif. Intell., April, 2024

Explainable AI in drug discovery: self-interpretable graph neural network for molecular property prediction using concept whitening.
Mach. Learn., April, 2024

2023
A self-interpretable module for deep image classification on small data.
Appl. Intell., April, 2023

Editorial: Ethical design of artificial intelligence-based systems for decision making.
Frontiers Artif. Intell., February, 2023

State of the Art of Visual Analytics for eXplainable Deep Learning.
Comput. Graph. Forum, February, 2023

An Overview of Environmental Features that Impact Deep Reinforcement Learning in Sparse-Reward Domains.
J. Artif. Intell. Res., 2023

Towards a fuller understanding of neurons with Clustered Compositional Explanations.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Visual Reward Machines.
Proceedings of the 17th International Workshop on Neural-Symbolic Learning and Reasoning, 2023

Memory Replay For Continual Learning With Spiking Neural Networks.
Proceedings of the 33rd IEEE International Workshop on Machine Learning for Signal Processing, 2023

Grounding LTLf Specifications in Image Sequences.
Proceedings of the 20th International Conference on Principles of Knowledge Representation and Reasoning, 2023

Understanding Deep RL Agent Decisions: a Novel Interpretable Approach with Trainable Prototypes.
Proceedings of the 4th Italian Workshop on Explainable Artificial Intelligence co-located with 22nd International Conference of the Italian Association for Artificial Intelligence(AIxIA 2023), 2023

2022
Outracing champion Gran Turismo drivers with deep reinforcement learning.
Nat., 2022

Ligand-based and structure-based studies to develop predictive models for SARS-CoV-2 main protease inhibitors through the 3d-qsar.com portal.
J. Comput. Aided Mol. Des., 2022

Semi-Supervised GCN for learning Molecular Structure-Activity Relationships.
CoRR, 2022

Molecule Generation from Input-Attributions over Graph Convolutional Networks.
CoRR, 2022

Grounding LTLf Specifications in Images.
Proceedings of the 16th International Workshop on Neural-Symbolic Learning and Reasoning as part of the 2nd International Joint Conference on Learning & Reasoning (IJCLR 2022), 2022

2021
LoOP: Iterative learning for optimistic planning on robots.
Robotics Auton. Syst., 2021

Agent-Based Markov Modeling for Improved COVID-19 Mitigation Policies.
J. Artif. Intell. Res., 2021

Memory Wrap: a Data-Efficient and Interpretable Extension to Image Classification Models.
CoRR, 2021

Autonomous Planetary Landing via Deep Reinforcement Learning and Transfer Learning.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2021

Multiagent Epidemiologic Inference through Realtime Contact Tracing.
Proceedings of the AAMAS '21: 20th International Conference on Autonomous Agents and Multiagent Systems, 2021

A Discussion about Explainable Inference on Sequential Data via Memory-Tracking.
Proceedings of the AIxIA 2021 Discussion Papers co-located with the the 20th International Conference of the Italian Association for Artificial Intelligence (AIxIA2021), 2021

Exploration-Intensive Distractors: Two Environment Proposals and a Benchmarking.
Proceedings of the AIxIA 2021 - Advances in Artificial Intelligence, 2021

Detection Accuracy for Evaluating Compositional Explanations of Units.
Proceedings of the AIxIA 2021 - Advances in Artificial Intelligence, 2021

Tafl-ES: Exploring Evolution Strategies for Asymmetrical Board Games.
Proceedings of the AIxIA 2021 - Advances in Artificial Intelligence, 2021

2020
Reinforcement Learning for Optimization of COVID-19 Mitigation policies.
CoRR, 2020

Explainable Inference on Sequential Data via Memory-Tracking.
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

GUESs: Generative modeling of Unknown Environments and Spatial Abstraction for Robots.
Proceedings of the 19th International Conference on Autonomous Agents and Multiagent Systems, 2020

2019
Cooperative Multi-agent Deep Reinforcement Learning in a 2 Versus 2 Free-Kick Task.
Proceedings of the RoboCup 2019: Robot World Cup XXIII [Sydney, 2019

Cooperative Multi-Agent Deep Reinforcement Learning in Soccer Domains.
Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems, 2019

S-AVE: Semantic Active Vision Exploration and Mapping of Indoor Environments for Mobile Robots.
Proceedings of the 6th Italian Workshop on Artificial Intelligence and Robotics co-located with the XVIII International Conference of the Italian Association for Artificial Intelligence (AI*IA 2019), 2019

2018
Efficient Long-term Mapping in Dynamic Environments.
Proceedings of the 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2018

Q-CP: Learning Action Values for Cooperative Planning.
Proceedings of the 2018 IEEE International Conference on Robotics and Automation, 2018

HI-VAL: Iterative Learning of Hierarchical Value Functions for Policy Generation.
Proceedings of the Intelligent Autonomous Systems 15, 2018

DOP: Deep Optimistic Planning with Approximate Value Function Evaluation.
Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems, 2018

2017
Interactive generation and learning of semantic-driven robot behaviors.
PhD thesis, 2017

2016
Living with robots: Interactive environmental knowledge acquisition.
Robotics Auton. Syst., 2016

Learning to Smooth with Bidirectional Predictive State Inference Machines.
Proceedings of the Thirty-Second Conference on Uncertainty in Artificial Intelligence, 2016

Using Monte Carlo Search with Data Aggregation to Improve Robot Soccer Policies.
Proceedings of the RoboCup 2016: Robot World Cup XX [Leipzig, Germany, June 30, 2016

STAM: A Framework for Spatio-Temporal Affordance Maps.
Proceedings of the Modelling and Simulation for Autonomous Systems, 2016

Improved Learning of Dynamics Models for Control.
Proceedings of the International Symposium on Experimental Robotics, 2016

Learning human-robot handovers through π-STAM: Policy improvement with spatio-temporal affordance maps.
Proceedings of the 16th IEEE-RAS International Conference on Humanoid Robots, 2016

Contexts for Symbiotic Autonomy: Semantic Mapping, Task Teaching and Social Robotics.
Proceedings of the Symbiotic Cognitive Systems, 2016

2015
A proposal for semantic map representation and evaluation.
Proceedings of the 2015 European Conference on Mobile Robots, 2015

Approaching Qualitative Spatial Reasoning About Distances and Directions in Robotics.
Proceedings of the AI*IA 2015, Advances in Artificial Intelligence, 2015

2014
Interactive Semantic Mapping: Experimental Evaluation.
Proceedings of the Experimental Robotics, 2014

Automatic Extraction of Structural Representations of Environments.
Proceedings of the Intelligent Autonomous Systems 13, 2014

Robust and Incremental Robot Learning by Imitation.
Proceedings of the Second Doctoral Workshop in Artificial Intelligence (DWAI 2014) An official workshop of the 13th Symposium of the Italian Association for Artificial Intelligence "Artificial Intelligence for Society and Economy" (AI*IA 2014), 2014

2013
Knowledge Representation for Robots through Human-Robot Interaction.
CoRR, 2013

On-line semantic mapping.
Proceedings of the 16th International Conference on Advanced Robotics, 2013


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