- receive input data divided into a plurality of blocks; 

- overfit a first neural encoder network for a first block of the data based on a baseline encoder network; 

- encode the first block by the first overfitted neural encoder network 

- overfit a second neural encoder network for at least one subsequent block of the data based on a combination of neural networks used for previous blocks and/or the baseline encoder network; and 

- encode the at least one subsequent block by the second overfitted neural encoder network. 

7. The apparatus of claim 6, further being caused to: 

- determine which one of the overfitted neural encoder networks performs the best; and 

- select such overfitted neural encoder network for a current block of the data. 

8. The apparatus according to claim 7, wherein the performance is determined according to one or both of the following aspects: a reconstruction quality or a bitrate. 

9. The apparatus according to any of the claims 6 to 8, wherein the data comprises image data, video data, or audio data. 

10.An apparatus comprising at least one processor, memory including computer program code, the memory and the computer program code configured to, with the at least one processor, cause the apparatus to: 

- receive a block residual defining a difference between an original block of data and a decoded block of the data; 

- based on the residual, recover the original block to be used as ground- truth data; and 

- overfit the neural decoder network based on the ground-truth data. 

11.The apparatus according to claim 10, further being caused to 

- receive a weight residual from a transmitter, the weight residual defining the difference between weights of the decoder before and after an overfitting. 

