Decodable and Sample Invariant Continuous Object Encoder

arXiv:2311.00187v3 Announce Type: replace
Abstract: We propose Hyper-Dimensional Function Encoding (HDFE). Given samples of a continuous object (e.g. a function), HDFE produces an explicit vector representation of the given object, invariant to the sample distribution and density. Sample distribution and density invariance enables HDFE to consistently encode continuous objects regardless of their sampling, and therefore allows neural networks to receive continuous objects as inputs for machine learning tasks, such as classification and regression. Besides, HDFE does not require any training …

abstract arxiv continuous cs.cv decodable distribution encode encoder encoding function objects representation sample samples sampling type vector