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pro vyhledávání: '"LAGERGREN, JENS"'
Mixture variational distributions in black box variational inference (BBVI) have demonstrated impressive results in challenging density estimation tasks. However, currently scaling the number of mixture components can lead to a linear increase in the
Externí odkaz:
http://arxiv.org/abs/2406.07083
Autor:
Nilsson, Alfred, Wijk, Klas, Gutha, Sai bharath chandra, Englesson, Erik, Hotti, Alexandra, Saccardi, Carlo, Kviman, Oskar, Lagergren, Jens, Vinuesa, Ricardo, Azizpour, Hossein
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 feature selection show promising results across a wide range of appli
Externí odkaz:
http://arxiv.org/abs/2403.00563
We present VBPI-Mixtures, an algorithm designed to enhance the accuracy of phylogenetic posterior distributions, particularly for tree-topology and branch-length approximations. Despite the Variational Bayesian Phylogenetic Inference (VBPI), a leadin
Externí odkaz:
http://arxiv.org/abs/2310.00941
We introduce a new optimization algorithm, termed contrastive adjustment, for learning Markov transition kernels whose stationary distribution matches the data distribution. Contrastive adjustment is not restricted to a particular family of transitio
Externí odkaz:
http://arxiv.org/abs/2303.05497
Over the years, sequential Monte Carlo (SMC) and, equivalently, particle filter (PF) theory has gained substantial attention from researchers. However, the performance of the resampling methodology, also known as offspring selection, has not advanced
Externí odkaz:
http://arxiv.org/abs/2212.12290
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 sampling literature. We then model the mixture components using separate e
Externí odkaz:
http://arxiv.org/abs/2209.15514
Autor:
Safinianaini, Negar, De Souza, Camila P.E., Roth, Andrew, Koptagel, Hazal, Toosi, Hosein, Lagergren, Jens
Publikováno v:
In Computational Biology and Chemistry December 2024 113
Phylogenetics is a classical methodology in computational biology that today has become highly relevant for medical investigation of single-cell data, e.g., in the context of cancer development. The exponential size of the tree space is, unfortunatel
Externí odkaz:
http://arxiv.org/abs/2203.01121
Publikováno v:
Proceedings of the 25th International Conference on Artificial Intelligence and Statistics (AISTATS) 2022, Valencia,Spain. PMLR: Volume 151
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). We propose the multiple importance sampling ELBO (MISELBO), a \text
Externí odkaz:
http://arxiv.org/abs/2202.10951
Publikováno v:
Transactions on Machine Learning Research, 2024
Web automation holds the potential to revolutionize how users interact with the digital world, offering unparalleled assistance and simplifying tasks via sophisticated computational methods. Central to this evolution is the web element nomination tas
Externí odkaz:
http://arxiv.org/abs/2111.02168