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07/30/2023
Redundancy-aware unsupervised rankings for collections of gene sets
The biological roles of gene sets are used to group them into collection...
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07/22/2022
Redundancy-aware unsupervised ranking based on game theory – application to gene enrichment analysis
Gene set collections are a common ground to study the enrichment of gene...
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07/18/2022
Boosting Multivariate Structured Additive Distributional Regression Models
We develop a model-based boosting approach for multivariate distribution...
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05/17/2022
Unsupervised Features Ranking via Coalitional Game Theory for Categorical Data
Not all real-world data are labeled, and when labels are not available, ...
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02/25/2022
Boosting Distributional Copula Regression
Capturing complex dependence structures between outcome variables (e.g.,...
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02/03/2022
Deselection of Base-Learners for Statistical Boosting – with an Application to Distributional Regression
We present a new procedure for enhanced variable selection for component...
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09/06/2021
Estimating the course of the COVID-19 pandemic in Germany via spline-based hierarchical modelling of death counts
The effective reproduction number is a key figure to monitor the course ...
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06/21/2021
Boundary Graph Neural Networks for 3D Simulations
The abundance of data has given machine learning huge momentum in natura...
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05/04/2021
Learning 3D Granular Flow Simulations
Recently, the application of machine learning models has gained momentum...
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11/04/2020
Estimating the evolution of effective infection fatality rates during the course of the COVID-19 pandemic in Germany
Several seroprevalence studies have been or are currently conducted in o...
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10/13/2020
Cross-Domain Few-Shot Learning by Representation Fusion
In order to quickly adapt to new data, few-shot learning aims at learnin...
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03/25/2020
Large-scale ligand-based virtual screening for SARS-CoV-2 inhibitors using deep neural networks
Due to the current severe acute respiratory syndrome coronavirus 2 (SARS...
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01/28/2019
RefCurv: A Software for the Construction of Pediatric Reference Curves
In medicine, reference curves serve as an important tool for everyday cl...
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10/24/2018
Extension of the Gradient Boosting Algorithm for Joint Modeling of Longitudinal and Time-to-Event data
In various data situations joint models are an efficient tool to analyze...
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10/06/2017
Gradient boosting in Markov-switching generalized additive models for location, scale and shape
We propose a novel class of flexible latent-state time series regression...
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06/08/2017
Self-Normalizing Neural Networks
Deep Learning has revolutionized vision via convolutional neural network...
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02/27/2017
An update on statistical boosting in biomedicine
Statistical boosting algorithms have triggered a lot of research during ...
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02/15/2017
Probing for sparse and fast variable selection with model-based boosting
We present a new variable selection method based on model-based gradient...
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09/09/2016
Boosting Joint Models for Longitudinal and Time-to-Event Data
Joint Models for longitudinal and time-to-event data have gained a lot o...
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03/04/2015
Toxicity Prediction using Deep Learning
Everyday we are exposed to various chemicals via food additives, cleanin...
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02/23/2015
Rectified Factor Networks
We propose rectified factor networks (RFNs) to efficiently construct ver...
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07/24/2013