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…