Here, := denotes assignment, H denotes the node features after neighbourhood aggregation and Z is the encoder output. The encoder is a chain of n classical multi-head attention blocks (mab) without positional encodings. The decoder component consists of a pooling by multi-head attention block (pma) (which uses a learnable seed vector s within a multi-head attention block to create an initial readout vector) that is further processed via a chain of m self-attention modules and a linear projection block (also called feedforward, ff). In contrast to typical set-based neural architectures that process individual items in isolation (most notably deep sets ), the presented adaptive readouts account for interactions between all the node representations generated by the neighbourhood aggregation scheme. A particularity of this architecture is that the dimension of the graph representation can be disentangled from the node output dimension and the aggregation scheme.