Flexible neural representation for physics prediction
Humans have a remarkable capacity to understand the physical dynamics of objects in their environment, flexibly capturing complex structures and interactions at multiple levels of detail. Inspired by this ability, we propose a hierarchical particle-based object representation that covers a wide vari...
| Main Authors: | , , , , , , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
Neural Information Processing Systems Foundation/Curran Associates
2020
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| Online Access: | https://hdl.handle.net/1721.1/126557 |