Graph-DQN: Fast Generalization To Novel Objects Using Prior Relational Knowledge

Humans have a remarkable ability to both generalize known actions to novel objects, and reason about novel objects once their relationship to known objects is understood. For example...


Hanlin Tang

Principal Engineer, Artificial Intelligence Products Group

View authors bio

Arjun Bansal

Vice President and General Manager, Artificial Intelligence Software and Lab at Intel

View authors bio

Varun Kumar

Related Content

Heuristics For Image Generation From Scene Graphs

Generating realistic images from scene graphs requires neural networks to be able to reason about object relationships and compositionality. Learning...

View publication

Label Efficient Audio Classification Through Multitask Learning And...

While deep learning has been incredibly successful in modeling tasks with large, carefully curated labeled datasets, its application to problems...

View publication

Hierarchical Policy Learning Is Sensitive To Goal Space...

Hierarchy in reinforcement learning agents allows for control at multiple time scales yielding improved sample efficiency, the ability to deal...

View publication

SPIGAN: Privileged Adversarial Learning from Simulation

Deep Learning for Computer Vision depends mainly on the source of supervision. Photo-realistic simulators can generate large-scale automatically labeled synthetic...

View publication

Stay Connected

Keep tabs on all the latest news with our monthly newsletter.