18 citations · 45 across the 21 of their papers we have counts for
3 papers · 1 filter
RECOMBINER: Robust and Enhanced Compression with Bayesian Implicit Neural Representations
Jiajun He, Gergely Flamich, Zongyu Guo +1
COMpression with Bayesian Implicit NEural Representations (COMBINER) is a recent data compression method that addresses a key inefficiency of previous Implicit Neural Representatio…
Minimal Random Code Learning with Mean-KL Parameterization
Jihao Andreas Lin, Gergely Flamich, José Miguel Hernández-Lobato
This paper studies the qualitative behavior and robustness of two variants of Minimal Random Code Learning (MIRACLE) used to compress variational Bayesian neural networks. MIRACLE…
Compression with Bayesian Implicit Neural Representations
Zongyu Guo, Gergely Flamich, Jiajun He +2
Many common types of data can be represented as functions that map coordinates to signal values, such as pixel locations to RGB values in the case of an image. Based on this view,…