72 citations · 330 across the 48 of their papers we have counts for
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stat.ML2023★ 2 cited
Modality-Agnostic Variational Compression of Implicit Neural Representations
Jonathan Richard Schwarz, Jihoon Tack, Yee Whye Teh +2
We introduce a modality-agnostic neural compression algorithm based on a functional view of data and parameterised as an Implicit Neural Representation (INR). Bridging the gap betw…
stat.ML2020★ 13 cited
Learning Bounds for Risk-sensitive Learning
Jaeho Lee, Sejun Park, Jinwoo Shin
In risk-sensitive learning, one aims to find a hypothesis that minimizes a risk-averse (or risk-seeking) measure of loss, instead of the standard expected loss. In this paper, we p…
stat.ML2018
Learning finite-dimensional coding schemes with nonlinear reconstruction maps
Jaeho Lee, Maxim Raginsky
This paper generalizes the Maurer--Pontil framework of finite-dimensional lossy coding schemes to the setting where a high-dimensional random vector is mapped to an element of a co…