1. A method for inferring patterns with a network comprising: providing a recursive network of sub-networks with a parent feature node and at least two child feature nodes; configuring nodes of the sub-networks with posterior distribution component; receiving data feature input at the final child feature nodes; propagating node activation through network layer hierarchy in a manner consistent with node connections of sub-networks of the network and the posterior prediction of child nodes, wherein propagating node activation comprises child feature nodes messaging a likelihood score to connected parent-specific child feature (PSCF) nodes; at a pool node of a sub-network, generating a likelihood score from the posterior distribution component and the likelihood score of connected PSCF nodes; at a parent feature node of the sub-network, generating a likelihood score from the posterior distribution component and the likelihood score of pool nodes connected to the parent feature node; enforcing an activation constraint between at least two nodes of a sub-network, wherein enforcing an activation constraint between at least two nodes comprises enforcing an activation constraint between a first PSCF node connected to a first pool node and a second PSCF node connected to a second pool node; and outputting parent feature node selection to an inferred output.