Search Results for author: Jens Lagergren

Found 11 papers, 8 papers with code

Efficient Mixture Learning in Black-Box Variational Inference

1 code implementation11 Jun 2024 Alexandra Hotti, Oskar Kviman, Ricky Molén, Víctor Elvira, Jens Lagergren

However, currently scaling the number of mixture components can lead to a linear increase in the number of learnable parameters and a quadratic increase in inference time due to the evaluation of the evidence lower bound (ELBO).

Density Estimation Variational Inference

Improved Variational Bayesian Phylogenetic Inference using Mixtures

1 code implementation2 Oct 2023 Oskar Kviman, Ricky Molén, Jens Lagergren

We present VBPI-Mixtures, an algorithm designed to enhance the accuracy of phylogenetic posterior distributions, particularly for tree-topology and branch-length approximations.

Density Estimation Variational Inference

Learning Stationary Markov Processes with Contrastive Adjustment

1 code implementation9 Mar 2023 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.

Image Inpainting

Statistical Distance Based Deterministic Offspring Selection in SMC Methods

no code implementations23 Dec 2022 Oskar Kviman, Hazal Koptagel, Harald Melin, Jens Lagergren

Over the years, sequential Monte Carlo (SMC) and, equivalently, particle filter (PF) theory has gained substantial attention from researchers.

Cooperation in the Latent Space: The Benefits of Adding Mixture Components in Variational Autoencoders

1 code implementation30 Sep 2022 Oskar Kviman, Ricky Molén, Alexandra Hotti, Semih Kurt, Víctor Elvira, Jens Lagergren

In this work, we also demonstrate that increasing the number of mixture components improves the latent-representation capabilities of the VAE on both image and single-cell datasets.

Variational Inference

VaiPhy: a Variational Inference Based Algorithm for Phylogeny

1 code implementation1 Mar 2022 Hazal Koptagel, Oskar Kviman, Harald Melin, Negar Safinianaini, Jens Lagergren

The exponential size of the tree space is, unfortunately, a substantial obstacle for Bayesian phylogenetic inference using Markov chain Monte Carlo based methods since these rely on local operations.

Density Estimation Variational Inference

Multiple Importance Sampling ELBO and Deep Ensembles of Variational Approximations

1 code implementation22 Feb 2022 Oskar Kviman, Harald Melin, Hazal Koptagel, Víctor Elvira, Jens Lagergren

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).

Density Estimation Variational Inference

The Klarna Product Page Dataset: Web Element Nomination with Graph Neural Networks and Large Language Models

1 code implementation3 Nov 2021 Alexandra Hotti, Riccardo Sven Risuleo, Stefan Magureanu, Aref Moradi, Jens Lagergren

To address this, we introduce the Klarna Product Page Dataset, a comprehensive and diverse collection of webpages that surpasses existing datasets in richness and variety.

Classification Language Modelling +2

Viewpoint and Topic Modeling of Current Events

no code implementations14 Aug 2016 Kerry Zhang, Jussi Karlgren, Cheng Zhang, Jens Lagergren

There are multiple sides to every story, and while statistical topic models have been highly successful at topically summarizing the stories in corpora of text documents, they do not explicitly address the issue of learning the different sides, the viewpoints, expressed in the documents.

Topic Models

A Global Structural EM Algorithm for a Model of Cancer Progression

no code implementations NeurIPS 2011 Ali Tofigh, Erik Sj̦Lund, Mattias H̦Glund, Jens Lagergren

Cancer has complex patterns of progression that include converging as well as diverging progressional pathways.

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