Dynamic Inference on Graphs using Structured Transition Models
Saumya Saxena,Oliver Kroemer,Saumya Saxena,Oliver Kroemer
Enabling robots to perform complex dynamic tasks such as picking up an object in one sweeping motion or pushing off a wall to quickly turn a corner is a challenging problem. The dynamic interactions implicit in these tasks are critical towards the successful execution of such tasks. Graph neural networks (GNNs) provide a principled way of learning the dynamics of interactive systems but can suffer...
