Search Results for author:
Found 3 papers, 1 papers with code
Creating Multimodal Interactive Agents with Imitation and Self-Supervised Learning
A common vision from science fiction is that robots will one day inhabit our physical spaces, sense the world as we do, assist our physical labours, and communicate with us through natural language.
Formalising Concepts as Grounded Abstractions
The mathematics of partial orders and lattices is a standard tool for modelling conceptual spaces (Ch. 2, Mitchell (1997), Ganter and Obiedkov (2016)); however, there is no formal work that we are aware of which defines a conceptual lattice on top of a representation that is induced using unsupervised deep learning (Goodfellow et al., 2016).
Grounded Language Learning Fast and Slow
Recent work has shown that large text-based neural language models, trained with conventional supervised learning objectives, acquire a surprising propensity for few- and one-shot learning.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
