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ORCIDRoberto Capobianco
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2020 – today
- 2024
[j11]Michela Proietti
, Alessio Ragno, Biagio La Rosa, Rino Ragno, Roberto Capobianco:
Explainable AI in drug discovery: self-interpretable graph neural network for molecular property prediction using concept whitening. Mach. Learn. 113(4): 2013-2044 (2024)- [j10]Alessio Ragno, Biagio La Rosa, Roberto Capobianco:
Prototype-Based Interpretable Graph Neural Networks. IEEE Trans. Artif. Intell. 5(4): 1486-1495 (2024) - [c39]Catherine Weaver, Roberto Capobianco, Peter R. Wurman, Peter Stone, Masayoshi Tomizuka:
Real-Time Trajectory Generation via Dynamic Movement Primitives for Autonomous Racing. ACC 2024: 352-359 - [c38]Alessio Ragno, Marc Plantevit, Céline Robardet, Roberto Capobianco:
Transparent Explainable Logic Layers. ECAI 2024: 914-921 - [c37]Elena Umili, Roberto Capobianco:
DeepDFA: Automata Learning through Neural Probabilistic Relaxations. ECAI 2024: 1051-1058 - [c36]Elena Umili, Francesco Argenziano, Roberto Capobianco:
Neural Reward Machines. ECAI 2024: 3055-3062 - [c35]Alessia Borghini, Federico Di Valerio, Alessio Ragno, Roberto Capobianco:
Identifying Candidates for Protein-Protein Interaction: A Focus on NKp46's Ligands. EXPLIMED@ECAI 2024 - [i15]Elena Umili, Roberto Capobianco:
DeepDFA: Automata Learning through Neural Probabilistic Relaxations. CoRR abs/2408.08622 (2024) - [i14]Elena Umili, Francesco Argenziano, Roberto Capobianco:
Neural Reward Machines. CoRR abs/2408.08677 (2024) - 2023
- [j9]Biagio La Rosa, Roberto Capobianco, Daniele Nardi:
A self-interpretable module for deep image classification on small data. Appl. Intell. 53(8): 9115-9147 (2023) - [j8]Biagio La Rosa, Graziano Blasilli, Romain Bourqui, David Auber, Giuseppe Santucci, Roberto Capobianco, Enrico Bertini, Romain Giot, Marco Angelini:
State of the Art of Visual Analytics for eXplainable Deep Learning. Comput. Graph. Forum 42(1): 319-355 (2023) - [j7]Giulio Biondi, Stefano Cagnoni, Roberto Capobianco, Valentina Franzoni, Francesca A. Lisi, Alfredo Milani, Jordi Vallverdú:
Editorial: Ethical design of artificial intelligence-based systems for decision making. Frontiers Artif. Intell. 6 (2023) - [j6]Jim Martin Catacora Ocana, Roberto Capobianco, Daniele Nardi:
An Overview of Environmental Features that Impact Deep Reinforcement Learning in Sparse-Reward Domains. J. Artif. Intell. Res. 76: 1181-1218 (2023) - [c34]Caterina Borzillo, Alessio Ragno, Roberto Capobianco:
Understanding Deep RL Agent Decisions: a Novel Interpretable Approach with Trainable Prototypes. XAI.it@AI*IA 2023: 1-14 - [c33]Elena Umili, Roberto Capobianco, Giuseppe De Giacomo:
Grounding LTLf Specifications in Image Sequences. KR 2023: 668-678 - [c32]Michela Proietti, Alessio Ragno, Roberto Capobianco:
Memory Replay For Continual Learning With Spiking Neural Networks. MLSP 2023: 1-6 - [c31]Elena Umili, Francesco Argenziano, Aymeric Barbin, Roberto Capobianco:
Visual Reward Machines. NeSy 2023: 255-267 - [c30]Biagio La Rosa, Leilani Gilpin, Roberto Capobianco:
Towards a fuller understanding of neurons with Clustered Compositional Explanations. NeurIPS 2023 - [i13]Biagio La Rosa, Leilani H. Gilpin, Roberto Capobianco:
Towards a fuller understanding of neurons with Clustered Compositional Explanations. CoRR abs/2310.18443 (2023) - 2022
- [j5]Eleonora Proia, Alessio Ragno, Lorenzo Antonini, Manuela Sabatino, Milan Mladenovic, Roberto Capobianco, Rino Ragno:
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. 36(7): 483-505 (2022) - [j4]Peter R. Wurman, Samuel Barrett, Kenta Kawamoto, James MacGlashan, Kaushik Subramanian, Thomas J. Walsh, Roberto Capobianco, Alisa Devlic, Franziska Eckert, Florian Fuchs, Leilani Gilpin, Piyush Khandelwal, Varun Raj Kompella, HaoChih Lin, Patrick MacAlpine, Declan Oller, Takuma Seno, Craig Sherstan, Michael D. Thomure, Houmehr Aghabozorgi, Leon Barrett, Rory Douglas, Dion Whitehead, Peter Dürr, Peter Stone, Michael Spranger, Hiroaki Kitano:
Outracing champion Gran Turismo drivers with deep reinforcement learning. Nat. 602(7896): 223-228 (2022) - [c29]Elena Umili, Roberto Capobianco, Giuseppe De Giacomo:
Grounding LTLf Specifications in Images. NeSy 2022: 45-63 - [i12]Dylan Savoia, Alessio Ragno, Roberto Capobianco:
Molecule Generation from Input-Attributions over Graph Convolutional Networks. CoRR abs/2202.05703 (2022) - [i11]Alessio Ragno, Dylan Savoia, Roberto Capobianco:
Semi-Supervised GCN for learning Molecular Structure-Activity Relationships. CoRR abs/2202.05704 (2022) - 2021
- [j3]Roberto Capobianco, Varun Raj Kompella, James Ault, Guni Sharon, Stacy Jong, Spencer J. Fox, Lauren Ancel Meyers, Peter R. Wurman, Peter Stone:
Agent-Based Markov Modeling for Improved COVID-19 Mitigation Policies. J. Artif. Intell. Res. 71: 953-992 (2021) - [j2]Francesco Riccio, Roberto Capobianco, Daniele Nardi:
LoOP: Iterative learning for optimistic planning on robots. Robotics Auton. Syst. 136: 103693 (2021) - [c28]Biagio La Rosa, Roberto Capobianco, Daniele Nardi:
A Discussion about Explainable Inference on Sequential Data via Memory-Tracking. DP@AI*IA 2021: 33-44 - [c27]Roberto Gallotta, Roberto Capobianco:
Tafl-ES: Exploring Evolution Strategies for Asymmetrical Board Games. AI*IA 2021: 46-58 - [c26]Jim Martin Catacora Ocana, Roberto Capobianco, Daniele Nardi:
Exploration-Intensive Distractors: Two Environment Proposals and a Benchmarking. AI*IA 2021: 413-428 - [c25]Sayo M. Makinwa, Biagio La Rosa, Roberto Capobianco:
Detection Accuracy for Evaluating Compositional Explanations of Units. AI*IA 2021: 550-563 - [c24]Guni Sharon, James Ault, Peter Stone, Varun Raj Kompella, Roberto Capobianco:
Multiagent Epidemiologic Inference through Realtime Contact Tracing. AAMAS 2021: 1182-1190 - [c23]Giulia Ciabatti, Shreyansh Daftry, Roberto Capobianco:
Autonomous Planetary Landing via Deep Reinforcement Learning and Transfer Learning. CVPR Workshops 2021: 2031-2038 - [i10]Biagio La Rosa, Roberto Capobianco, Daniele Nardi:
Memory Wrap: a Data-Efficient and Interpretable Extension to Image Classification Models. CoRR abs/2106.01440 (2021) - [i9]Sayo M. Makinwa, Biagio La Rosa, Roberto Capobianco:
Detection Accuracy for Evaluating Compositional Explanations of Units. CoRR abs/2109.07804 (2021) - 2020
- [c22]Varun Raj Kompella, Roberto Capobianco, Stacy Jong, Jonathan Browne, Spencer J. Fox, Lauren Ancel Meyers, Peter R. Wurman, Peter Stone:
Reinforcement Learning for Optimization of COVID-19 Mitigation Policies. AI4SG@AAAI Fall Symposium 2020 - [c21]Francesco Riccio, Roberto Capobianco, Daniele Nardi:
GUESs: Generative modeling of Unknown Environments and Spatial Abstraction for Robots. AAMAS 2020: 1978-1980 - [c20]Biagio La Rosa, Roberto Capobianco, Daniele Nardi:
Explainable Inference on Sequential Data via Memory-Tracking. IJCAI 2020: 2006-2013 - [i8]Varun Raj Kompella, Roberto Capobianco, Stacy Jong, Jonathan Browne, Spencer J. Fox, Lauren Ancel Meyers, Peter R. Wurman, Peter Stone:
Reinforcement Learning for Optimization of COVID-19 Mitigation policies. CoRR abs/2010.10560 (2020)
2010 – 2019
- 2019
- [c19]José V. Jaramillo, Roberto Capobianco, Francesco Riccio, Daniele Nardi:
S-AVE: Semantic Active Vision Exploration and Mapping of Indoor Environments for Mobile Robots. AIRO@AI*IA 2019: 47-52 - [c18]Jim Martin Catacora Ocana, Francesco Riccio, Roberto Capobianco, Daniele Nardi:
Cooperative Multi-Agent Deep Reinforcement Learning in Soccer Domains. AAMAS 2019: 1865-1867 - [c17]Jim Martin Catacora Ocana, Francesco Riccio, Roberto Capobianco, Daniele Nardi:
Cooperative Multi-agent Deep Reinforcement Learning in a 2 Versus 2 Free-Kick Task. RoboCup 2019: 44-57 - 2018
- [c16]Francesco Riccio, Roberto Capobianco, Daniele Nardi:
DOP: Deep Optimistic Planning with Approximate Value Function Evaluation. AAMAS 2018: 2210-2212 - [c15]Roberto Capobianco, Francesco Riccio, Daniele Nardi:
HI-VAL: Iterative Learning of Hierarchical Value Functions for Policy Generation. IAS 2018: 414-427 - [c14]Francesco Riccio, Roberto Capobianco, Daniele Nardi:
Q-CP: Learning Action Values for Cooperative Planning. ICRA 2018: 6469-6475 - [c13]Maria Teresa Lazaro, Roberto Capobianco, Giorgio Grisetti:
Efficient Long-term Mapping in Dynamic Environments. IROS 2018: 153-160 - [i7]Francesco Riccio, Roberto Capobianco, Daniele Nardi:
Q-CP: Learning Action Values for Cooperative Planning. CoRR abs/1803.00297 (2018) - [i6]Francesco Riccio, Roberto Capobianco, Daniele Nardi:
DOP: Deep Optimistic Planning with Approximate Value Function Evaluation. CoRR abs/1803.08501 (2018) - 2017
- [b1]Roberto Capobianco:
Interactive generation and learning of semantic-driven robot behaviors. Sapienza University of Rome, Italy, 2017 - 2016
- [j1]Guglielmo Gemignani, Roberto Capobianco, Emanuele Bastianelli, Domenico Daniele Bloisi, Luca Iocchi, Daniele Nardi:
Living with robots: Interactive environmental knowledge acquisition. Robotics Auton. Syst. 78: 1-16 (2016) - [c12]Roberto Capobianco, Guglielmo Gemignani, Luca Iocchi, Daniele Nardi, Francesco Riccio, Andrea Vanzo:
Contexts for Symbiotic Autonomy: Semantic Mapping, Task Teaching and Social Robotics. AAAI Workshop: Symbiotic Cognitive Systems 2016 - [c11]Francesco Riccio, Roberto Capobianco, Daniele Nardi:
Learning human-robot handovers through π-STAM: Policy improvement with spatio-temporal affordance maps. Humanoids 2016: 857-863 - [c10]Arun Venkatraman, Roberto Capobianco, Lerrel Pinto, Martial Hebert, Daniele Nardi, J. Andrew Bagnell:
Improved Learning of Dynamics Models for Control. ISER 2016: 703-713 - [c9]Francesco Riccio, Roberto Capobianco, Marc Hanheide, Daniele Nardi:
STAM: A Framework for Spatio-Temporal Affordance Maps. MESAS 2016: 271-280 - [c8]Francesco Riccio, Roberto Capobianco, Daniele Nardi:
Using Monte Carlo Search with Data Aggregation to Improve Robot Soccer Policies. RoboCup 2016: 256-267 - [c7]Wen Sun, Roberto Capobianco, Geoffrey J. Gordon, J. Andrew Bagnell, Byron Boots:
Learning to Smooth with Bidirectional Predictive State Inference Machines. UAI 2016 - [i5]Francesco Riccio, Roberto Capobianco, Daniele Nardi:
Using Monte Carlo Search With Data Aggregation to Improve Robot Soccer Policies. CoRR abs/1606.00285 (2016) - [i4]Roberto Capobianco, Jacopo Serafin, Johann Dichtl, Giorgio Grisetti, Luca Iocchi, Daniele Nardi:
A Proposal for Semantic Map Representation and Evaluation. CoRR abs/1606.03719 (2016) - [i3]Francesco Riccio, Roberto Capobianco, Marc Hanheide, Daniele Nardi:
STAM: A Framework for Spatio-Temporal Affordance Maps. CoRR abs/1607.00354 (2016) - [i2]Francesco Riccio, Roberto Capobianco, Daniele Nardi:
Learning Human-Robot Handovers Through π-STAM: Policy Improvement With Spatio-Temporal Affordance Maps. CoRR abs/1610.02609 (2016) - 2015
- [c6]Guglielmo Gemignani, Roberto Capobianco, Daniele Nardi:
Approaching Qualitative Spatial Reasoning About Distances and Directions in Robotics. AI*IA 2015: 452-464 - [c5]Roberto Capobianco, Jacopo Serafin, Johann Dichtl, Giorgio Grisetti, Luca Iocchi, Daniele Nardi:
A proposal for semantic map representation and evaluation. ECMR 2015: 1-6 - 2014
- [c4]Roberto Capobianco:
Robust and Incremental Robot Learning by Imitation. DWAI@AI*IA 2014: 82-91 - [c3]Roberto Capobianco, Guglielmo Gemignani, Domenico Daniele Bloisi, Daniele Nardi, Luca Iocchi:
Automatic Extraction of Structural Representations of Environments. IAS 2014: 721-733 - [c2]Guglielmo Gemignani, Daniele Nardi, Domenico Daniele Bloisi, Roberto Capobianco, Luca Iocchi:
Interactive Semantic Mapping: Experimental Evaluation. ISER 2014: 339-355 - 2013
- [c1]Emanuele Bastianelli, Domenico Daniele Bloisi, Roberto Capobianco, F. Cossu, Guglielmo Gemignani, Luca Iocchi, Daniele Nardi:
On-line semantic mapping. ICAR 2013: 1-6 - [i1]Emanuele Bastianelli, Domenico Bloisi, Roberto Capobianco, Guglielmo Gemignani, Luca Iocchi, Daniele Nardi:
Knowledge Representation for Robots through Human-Robot Interaction. CoRR abs/1307.7351 (2013)
Coauthor Index
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