4 citations · 8 across the 4 of their papers we have counts for
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Efficient Mixture Learning in Black-Box Variational Inference
Alexandra Hotti, Oskar Kviman, Ricky Molén +2
Mixture variational distributions in black box variational inference (BBVI) have demonstrated impressive results in challenging density estimation tasks. However, currently scaling…
Indirectly Parameterized Concrete Autoencoders
Alfred Nilsson, Klas Wijk, Sai bharath chandra Gutha +7
Feature selection is a crucial task in settings where data is high-dimensional or acquiring the full set of features is costly. Recent developments in neural network-based embedded…
Cooperation in the Latent Space: The Benefits of Adding Mixture Components in Variational Autoencoders
Oskar Kviman, Ricky Molén, Alexandra Hotti +3
In this paper, we show how the mixture components cooperate when they jointly adapt to maximize the ELBO. We build upon recent advances in the multiple and adaptive importance samp…
The Klarna Product Page Dataset: Web Element Nomination with Graph Neural Networks and Large Language Models
Alexandra Hotti, Riccardo Sven Risuleo, Stefan Magureanu +2
Web automation holds the potential to revolutionize how users interact with the digital world, offering unparalleled assistance and simplifying tasks via sophisticated computationa…