RECOMBINER: Robust and Enhanced Compression with Bayesian Implicit Neural Representations

arXiv:2309.17182v2 Announce Type: replace
Abstract: COMpression with Bayesian Implicit NEural Representations (COMBINER) is a recent data compression method that addresses a key inefficiency of previous Implicit Neural Representation (INR)-based approaches: it avoids quantization and enables direct optimization of the rate-distortion performance. However, COMBINER still has significant limitations: 1) it uses factorized priors and posterior approximations that lack flexibility; 2) it cannot effectively adapt to local deviations from global patterns in the data; and 3) its performance can be susceptible to …

arxiv bayesian compression cs.lg implicit neural representations robust type