docstring for QuantMeasure.

r"""The graph isomorphism operator from the `"How Powerful are Graph Neural Networks?" <https://arxiv.org/abs/1810.00826>`_ paper .. math::

r"""The neighbor sampler from the `"Inductive Representation Learning on Large Graphs" <https://arxiv.org/abs/1706.02216>`_ paper, which allows

r"""The graph convolutional operator from the `"Semi-supervised Classification with Graph Convolutional Networks" <https://arxiv.org/abs/1609.

docstring for QConv2d.

r"""The graph attentional operator from the `"Graph Attention Networks" <https://arxiv.org/abs/1710.10903>`_ paper .. math:: \mathbf{

r"""The GraphSAGE operator from the `"Inductive Representation Learning on Large Graphs" <https://arxiv.org/abs/1706.02216>`_ paper .. math::

docstring for QConv2d.

docstring for QConv2d.

docstring for QConv2d.

r"""The neighbor sampler from the `"Inductive Representation Learning on Large Graphs" <https://arxiv.org/abs/1706.02216>`_ paper, which allows

r"""The graph attentional operator from the `"Graph Attention Networks" <https://arxiv.org/abs/1710.10903>`_ paper .. math:: \mathbf{

r"""The modified :class:`GINConv` operator from the `"Strategies for Pre-training Graph Neural Networks" <https://arxiv.org/abs/1905.12265>`_

docstring for QConv2d.

docstring for QConv2d.

r"""A data loader that randomly samples nodes within a graph and returns their induced subgraph. .. note:: For an example of using :ob

r"""A data loader that randomly samples nodes within a graph and returns their induced subgraph. .. note:: For an example of using :ob