The following pages link to Graph Representation Learning (Q5126696):
Displaying 19 items.
- A gentle introduction to deep learning for graphs (Q2055049) (← links)
- On the expressive power of message-passing neural networks as global feature map transformers (Q2103899) (← links)
- Inclusion of domain-knowledge into GNNs using mode-directed inverse entailment (Q2127250) (← links)
- Transferability of graph neural networks: an extended graphon approach (Q2677834) (← links)
- Generalized Learning Graph Quantization (Q3003455) (← links)
- (Q5053257) (← links)
- Graph representation learning for popularity prediction problem: A survey (Q5057725) (← links)
- Heterogeneous Graph Representation Learning and Applications (Q5159260) (← links)
- Learning physical properties of anomalous random walks using graph neural networks (Q5874132) (← links)
- Deep learning and geometric deep learning: An introduction for mathematicians and physicists (Q6144784) (← links)
- Entropic Optimal Transport on Random Graphs (Q6148350) (← links)
- Graph neural networks induced by concept lattices for classification (Q6157222) (← links)
- Fault detection and isolation of multi-variate time series data using spectral weighted graph auto-encoders (Q6168965) (← links)
- A HYBRID MEMBERSHIP LATENT DISTANCE MODEL FOR UNSIGNED AND SIGNED INTEGER WEIGHTED NETWORKS (Q6203416) (← links)
- Structural iterative lexicographic autoencoded node representation (Q6486127) (← links)
- Embedding graphs on Grassmann manifold (Q6488709) (← links)
- A microstructure-based graph neural network for accelerating multiscale simulations (Q6557762) (← links)
- One-shot learning for MIPs with SOS1 constraints (Q6579097) (← links)
- A hybrid numerical methodology coupling reduced order modeling and graph neural networks for non-parametric geometries: applications to structural dynamics problems (Q6595908) (← links)
