4 citations · 4 across the 2 of their papers we have counts for
3 papers
MHVAE: a Human-Inspired Deep Hierarchical Generative Model for Multimodal Representation Learning
Miguel Vasco, Francisco S. Melo, Ana Paiva
Humans are able to create rich representations of their external reality. Their internal representations allow for cross-modality inference, where available perceptions can induce…
Playing Games in the Dark: An approach for cross-modality transfer in reinforcement learning
Rui Silva, Miguel Vasco, Francisco S. Melo +2
In this work we explore the use of latent representations obtained from multiple input sensory modalities (such as images or sounds) in allowing an agent to learn and exploit polic…
Learning multimodal representations for sample-efficient recognition of human actions
Miguel Vasco, Francisco S. Melo, David Martins de Matos +2
Humans interact in rich and diverse ways with the environment. However, the representation of such behavior by artificial agents is often limited. In this work we present \textit{m…