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04/25/2023
Discovering Graph Generation Algorithms
We provide a novel approach to construct generative models for graphs. I...
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11/20/2022
Automating Rigid Origami Design
While rigid origami has shown potential in a large diversity of engineer...
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10/04/2022
Diffusion Models for Graphs Benefit From Discrete State Spaces
Denoising diffusion probabilistic models and score matching models have ...
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06/22/2022
Agent-based Graph Neural Networks
We present a novel graph neural network we call AgentNet, which is desig...
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05/26/2022
DT+GNN: A Fully Explainable Graph Neural Network using Decision Trees
We propose the fully explainable Decision Tree Graph Neural Network (DT+...
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04/04/2022
SPECTRE : Spectral Conditioning Helps to Overcome the Expressivity Limits of One-shot Graph Generators
We approach the graph generation problem from a spectral perspective by ...
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11/11/2021
DropGNN: Random Dropouts Increase the Expressiveness of Graph Neural Networks
This paper studies Dropout Graph Neural Networks (DropGNNs), a new appro...
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09/27/2021
On Isotropy Calibration of Transformers
Different studies of the embedding space of transformer models suggest t...
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10/14/2020