Måns Magnusson | DeepAI

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∙ 09/21/2023

The Cambridge Law Corpus: A Corpus for Legal AI Research

We introduce the Cambridge Law Corpus (CLC), a corpus for legal AI resea...

0 Andreas Östling, et al. ∙

∙ 03/25/2022

Probabilistic Embeddings with Laplacian Graph Priors

We introduce probabilistic embeddings using Laplacian priors (PELP). The...

0 Väinö Yrjänäinen, et al. ∙

∙ 01/25/2021

Rapid mixing in unimodal landscapes and efficient simulatedannealing for multimodal distributions

We consider nearest neighbor weighted random walks on the d-dimensional ...

0 Johan Jonasson, et al. ∙

∙ 09/01/2020

Robust, Accurate Stochastic Optimization for Variational Inference

We consider the problem of fitting variational posterior approximations ...

8 Akash Kumar Dhaka, et al. ∙

∙ 08/25/2020

Unbiased estimator for the variance of the leave-one-out cross-validation estimator for a Bayesian normal model with fixed variance

When evaluating and comparing models using leave-one-out cross-validatio...

0 Tuomas Sivula, et al. ∙

∙ 08/24/2020

Uncertainty in Bayesian Leave-One-Out Cross-Validation Based Model Comparison

Leave-one-out cross-validation (LOO-CV) is a popular method for comparin...

0 Tuomas Sivula, et al. ∙

∙ 03/09/2020

When are Bayesian model probabilities overconfident?

Bayesian model comparison is often based on the posterior distribution o...

0 Oscar Oelrich, et al. ∙

∙ 01/03/2020

Leave-One-Out Cross-Validation for Bayesian Model Comparison in Large Data

Recently, new methods for model assessment, based on subsampling and pos...

0 Måns Magnusson, et al. ∙

∙ 09/03/2019

Interpretable Word Embeddings via Informative Priors

Word embeddings have demonstrated strong performance on NLP tasks. Howev...

0 Miriam Hurtado Bodell, et al. ∙

∙ 06/06/2019

Sparse Parallel Training of Hierarchical Dirichlet Process Topic Models

Nonparametric extensions of topic models such as Latent Dirichlet Alloca...

0 Alexander Terenin, et al. ∙

∙ 04/24/2019

Bayesian leave-one-out cross-validation for large data

Model inference, such as model comparison, model checking, and model sel...

20 Måns Magnusson, et al. ∙

∙ 05/18/2018

Multivariate Analysis of Orthogonal Range Searching and Graph Distances Parameterized by Treewidth

We show that the eccentricities, diameter, radius, and Wiener index of a...

0 Karl Bringmann, et al. ∙

∙ 04/12/2017

Polya Urn Latent Dirichlet Allocation: a doubly sparse massively parallel sampler

Latent Dirichlet Allocation (LDA) is a topic model widely used in natura...

0 Alexander Terenin, et al. ∙

∙ 01/31/2016

DOLDA - a regularized supervised topic model for high-dimensional multi-class regression

Generating user interpretable multi-class predictions in data rich envir...

0 Måns Magnusson, et al. ∙

∙ 06/11/2015

Sparse Partially Collapsed MCMC for Parallel Inference in Topic Models

Topic models, and more specifically the class of Latent Dirichlet Alloca...

0 Måns Magnusson, et al. ∙

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