Abstract: Disclosed is a decoder for decoding parameters of a neural network, configured to obtain a plurality of neural network parameters of the neural network on the basis of an encoded bitstream, to obtain, e.g. to receive; e.g. to extract from an encoded bitstream, a node information describing a node of a parameter update tree, wherein the node information has a parent node identifier, which is, for example, a unique parent node identifier, for example an integer number, a string, and/or a cryptographic hash, and wherein the node information has a parameter update information, e.g. one or more update instructions, for example a difference signal between initial neural network parameters and a newer version thereof, e.g. corresponding to a child node of the update tree, and to derive one or more neural network parameters using parameter information of a parent node identified by the parent node identifier and using the parameter update information.

Abstract: Embodiments according to the invention comprise an apparatus for decoding neural network parameters, which define a neural network. The apparatus may, optionally, be configured to obtain, e.g. to decode, parameters of a base model, e.g. NB, of the neural network which define one or more layers, e.g. base layers, of the neural network. Furthermore, the apparatus is configured to decode an update model, e.g. NU1 to NUK, which defines a modification of one or more layers, e.g. base layers, of the neural network, and the apparatus is configured modify parameters of a base model of the neural network using the update model, in order to obtain an updated model, e.g. designated as “new model” comprising new model layers LNkj. Moreover, the apparatus is configured to evaluate a skip information, e.g. a skip_row_flag and/or a skip_column_flag, indicating whether a sequence, e.g. a row, or a column or a block, of parameters of the update model is zero or not.