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05/25/2023
Fractional Polynomials Models as Special Cases of Bayesian Generalized Nonlinear Models
We propose a framework for fitting fractional polynomials models as spec...
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05/05/2023
Sparsifying Bayesian neural networks with latent binary variables and normalizing flows
Artificial neural networks (ANNs) are powerful machine learning methods ...
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05/01/2023
Variational Inference for Bayesian Neural Networks under Model and Parameter Uncertainty
Bayesian neural networks (BNNs) have recently regained a significant amo...
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10/11/2021
Reversible Genetically Modified Mode Jumping MCMC
In this paper, we introduce a reversible version of a genetically modifi...
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04/19/2021
skweak: Weak Supervision Made Easy for NLP
We present skweak, a versatile, Python-based software toolkit enabling N...
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05/01/2020
Rejoinder for the discussion of the paper "A novel algorithmic approach to Bayesian Logic Regression"
In this rejoinder we summarize the comments, questions and remarks on th...
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04/30/2020
Named Entity Recognition without Labelled Data: A Weak Supervision Approach
Named Entity Recognition (NER) performance often degrades rapidly when a...
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04/28/2020
A Bayesian binomial regression model with latent Gaussian processes for modelling DNA methylation
Epigenetic observations are represented by the total number of reads fro...
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03/05/2020
Flexible Bayesian Nonlinear Model Configuration
Regression models are used in a wide range of applications providing a p...
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12/20/2019
An adaptive simulated annealing EM algorithm for inference on non-homogeneous hidden Markov models
Non-homogeneous hidden Markov models (NHHMM) are a subclass of dependent...
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03/18/2019
Combining Model and Parameter Uncertainty in Bayesian Neural Networks
Bayesian neural networks (BNNs) have recently regained a significant amo...
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06/06/2018
