Publications

Journal Papers (3)

Leveraging Hierarchy in Multimodal Generative Models for Effective Cross-Modality Inference

Miguel Vasco, Hang Yin, Francisco S. Melo, and Ana Paiva. Neural Networks (2021 Special Issue on AI and Brain Science: Brain-inspired AI), 146, 238-255. [pdf]

Project INSIDE: towards autonomous semi-unstructured human–robot social interaction in autism therapy

Francisco S. Melo, Alberto Sardinha, David Belo, Marta Couto, Miguel Faria, Anabela Farias, Hugo Gambôa, Cátia Jesus, Mithun Kinarullathil, Pedro Lima, Luís Luz, André Mateus, Isabel Melo, Plinio Moreno, Daniel Osório, Ana Paiva, Jhielson Pimentel, João Rodrigues, Pedro Sequeira, Rubén Solera-Ureña, Miguel Vasco, Manuela Veloso and Rodrigo Ventura. Artificial intelligence in medicine, 96, 198-216. [pdf]

3D map distribution of metallic nanoparticles in whole cells using MeV ion microscopy

Miguel Vasco, Luís Alves, Victoria Corregidor, Daniel Correia, Cláudia P. Godinho, Isabel Sá‐Correia, Andrew Bettiol, Frank Watt, and Teresa Pinheiro. Journal of microscopy, 267(2), pp.227-236. [pdf]

Conference Paper (7)

Perceive, Represent, Generate: Translating Multimodal Information to Robotic Motion Trajectories

Fabio Vital, Miguel Vasco, Alberto Sardinha, and Francisco S. Melo. in 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) - To appear.

Geometric Multimodal Contrastive Representation Learning

Petra Poklukar*, Miguel Vasco*, Hang Yin, Francisco S. Melo, Ana Paiva, and Danica Kragic. International Conference on Machine Learning. PMLR, 2022. (pp. 17782-17800). [pdf]

How to Sense the World: Leveraging Hierarchy in Multimodal Perception for Robust Reinforcement Learning Agents

Miguel Vasco, Hang Yin, Francisco S. Melo and Ana Paiva. In Proceedings of the 21th International Conference on Autonomous Agents and MultiAgent Systems (pp. 1301-1309). [pdf]

Exploiting Symmetry in Human Robot-Assisted Dressing Using Reinforcement Learning

Pedro Ildefonso, Pedro Remédios, Rui Silva, Miguel Vasco, Francisco S. Melo, Ana Paiva, and Manuela Veloso. In EPIA Conference on Artificial Intelligence, pp. 405-417. Springer, Cham, 2021. [pdf]

Explainable Agency by Revealing Suboptimality in Child-Robot Learning Scenarios

Silvia Tulli, Marta Couto, Miguel Vasco, Elmira Yadollahi, Francisco S. Melo, and Ana Paiva. In International Conference on Social Robotics (pp. 23-35). Springer, Cham. (Best Paper Award) [pdf]

Playing Games in the Dark: An approach for cross-modality transfer in reinforcement learning

Rui Silva, Miguel Vasco, Francisco S. Melo, Ana Paiva, and Manuela Veloso. In Proceedings of the 19th International Conference on Autonomous Agents and MultiAgent Systems (pp. 1260-1268). [pdf]

Learning multimodal representations for sample-efficient recognition of human actions

Miguel Vasco, Francisco S Melo, David Martins de Matos, Ana Paiva, and Tetsunari Inamura. In 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (pp. 4288-4293). IEEE. [pdf]

Refereed Extended Abstract (2)

Multimodal Representation Learning for Robotic Cross-Modality Policy Transfer

Miguel Vasco. In Proceedings of the 19th International Conference on Autonomous Agents and MultiAgent Systems (pp. 2225-2227). Doctoral Consortium. [pdf]

Online Motion Concept Learning: A Novel Algorithm for Sample-Efficient Learning and Recognition of Human Actions

Miguel Vasco, Francisco S Melo, David Martins de Matos, Ana Paiva, and Tetsunari Inamura. In Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems (pp. 2244-2246). [pdf]

Preprints (1)

MHVAE: a Human-Inspired Deep Hierarchical Generative Model for Multimodal Representation Learning

Miguel Vasco, Francisco S Melo, and Ana Paiva. arXiv preprint arXiv:2006.02991. [pdf]

All images created with Dall-E (Open-AI 2022) and available here.