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20232026
most citedIdentifiable Feature Learning for Spatial Data with Nonlinear ICA

2 citations · 2 across the 6 of their papers we have counts for

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stat.ML2023★ 2 cited

Identifiable Feature Learning for Spatial Data with Nonlinear ICA

Hermanni Hälvä, Jonathan So, Richard E. Turner +1

Recently, nonlinear ICA has surfaced as a popular alternative to the many heuristic models used in deep representation learning and disentanglement. An advantage of nonlinear ICA i…

stat.ML2023

Optimising Distributions with Natural Gradient Surrogates

Jonathan So, Richard E. Turner

Natural gradient methods have been used to optimise the parameters of probability distributions in a variety of settings, often resulting in fast-converging procedures. Unfortunate…