4 citations · 15 across the 7 of their papers we have counts for
4 papers · 1 filter
Learning Stationary Markov Processes with Contrastive Adjustment
Ludvig Bergenstråhle, Jens Lagergren, Joakim Lundeberg
We introduce a new optimization algorithm, termed contrastive adjustment, for learning Markov transition kernels whose stationary distribution matches the data distribution. Contra…
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…
Multiple Importance Sampling ELBO and Deep Ensembles of Variational Approximations
Oskar Kviman, Harald Melin, Hazal Koptagel +2
In variational inference (VI), the marginal log-likelihood is estimated using the standard evidence lower bound (ELBO), or improved versions as the importance weighted ELBO (IWELBO…
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…