3 papers
cs.LG2020
Equivariant Maps for Hierarchical Structures
Renhao Wang, Marjan Albooyeh, Siamak Ravanbakhsh
While using invariant and equivariant maps, it is possible to apply deep learning to a range of primitive data structures, a formalism for dealing with hierarchy is lacking. This i…
cs.LG2020
Out-of-Sample Representation Learning for Multi-Relational Graphs
Marjan Albooyeh, Rishab Goel, Seyed Mehran Kazemi
Many important problems can be formulated as reasoning in knowledge graphs. Representation learning has proved extremely effective for transductive reasoning, in which one needs to…
cs.LG2019
Incidence Networks for Geometric Deep Learning
Marjan Albooyeh, Daniele Bertolini, Siamak Ravanbakhsh
Sparse incidence tensors can represent a variety of structured data. For example, we may represent attributed graphs using their node-node, node-edge, or edge-edge incidence matric…