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rusty1s committed Jul 30, 2019
1 parent ee67aaa commit d5c3918e833341ab91842d501e23c5cc43159f80
Showing with 3 additions and 3 deletions.
  1. +1 −1 README.md
  2. +2 −2 torch_geometric/nn/conv/__init__.py
@@ -98,7 +98,7 @@ In detail, the following methods are currently implemented:
* **[Deep Graph Infomax](https://pytorch-geometric.readthedocs.io/en/latest/modules/nn.html#torch_geometric.nn.models.DeepGraphInfomax)** from Veličković *et al.*: [Deep Graph Infomax](https://arxiv.org/abs/1809.10341) (ICLR 2019)
* All variants of **[Graph Auto-Encoders](https://pytorch-geometric.readthedocs.io/en/latest/modules/nn.html#torch_geometric.nn.models.GAE)** from Kipf and Welling: [Variational Graph Auto-Encoders](https://arxiv.org/abs/1611.07308) (NIPS-W 2016) and Pan *et al.*: [Adversarially Regularized Graph Autoencoder for Graph Embedding](https://arxiv.org/abs/1802.04407) (IJCAI 2018)
* **[RENet](https://pytorch-geometric.readthedocs.io/en/latest/modules/nn.html#torch_geometric.nn.models.RENet)** from Jin *et al.*: [Recurrent Event Network for Reasoning over Temporal Knowledge Graphs](https://arxiv.org/abs/1904.05530) (ICLR-W 2019)
* **[GraphUNet](https://pytorch-geometric.readthedocs.io/en/latest/modules/nn.html#torch_geometric.nn.model.GraphUNet)** from Gao and Ji: [Graph U-Nets](https://arxiv.org/abs/1905.05178) (ICML 2019)
* **[GraphUNet](https://pytorch-geometric.readthedocs.io/en/latest/modules/nn.html#torch_geometric.nn.models.GraphUNet)** from Gao and Ji: [Graph U-Nets](https://arxiv.org/abs/1905.05178) (ICML 2019)
* **[NeighborSampler](https://pytorch-geometric.readthedocs.io/en/latest/modules/nn.html#torch_geometric.nn.data.NeighborSampler)** from Hamilton *et al.*: [Inductive Representation Learning on Large Graphs](https://arxiv.org/abs/1706.02216) (NIPS 2017)
--------------------------------------------------------------------------------
@@ -6,6 +6,7 @@
from .gated_graph_conv import GatedGraphConv
from .gat_conv import GATConv
from .agnn_conv import AGNNConv
from .tag_conv import TAGConv
from .gin_conv import GINConv
from .arma_conv import ARMAConv
from .sg_conv import SGConv
@@ -22,7 +23,6 @@
from .ppf_conv import PPFConv
from .feast_conv import FeaStConv
from .hypergraph_conv import HypergraphConv
from .tag_conv import TAGConv

__all__ = [
'MessagePassing',
@@ -33,6 +33,7 @@
'GatedGraphConv',
'GATConv',
'AGNNConv',
'TAGConv',
'GINConv',
'ARMAConv',
'SGConv',
@@ -51,5 +52,4 @@
'PPFConv',
'FeaStConv',
'HypergraphConv',
'TAGConv',
]

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