Thomas Kneib

According to our database, Thomas Kneib authored at least 43 papers between 2006 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Probabilistic Topic Modelling with Transformer Representations.

Arik Reuter, Anton Thielmann, Christoph Weisser, Benjamin Säfken, Thomas Kneib

CoRR, 2024

2023

Spatial joint models through Bayesian structured piecewise additive joint modelling for longitudinal and time-to-event data.

Anja Rappl, Thomas Kneib, Stefan Lang, Elisabeth Bergherr

Stat. Comput., December, 2023

Multivariate distributional stochastic frontier models.

Rouven Schmidt, Thomas Kneib

Comput. Stat. Data Anal., November, 2023

Pseudo-document simulation for comparing LDA, GSDMM and GPM topic models on short and sparse text using Twitter data.

Christoph Weisser, Christoph Gerloff, Anton Thielmann, Andre Python, Arik Reuter, Thomas Kneib, Benjamin Säfken

Comput. Stat., June, 2023

Probabilistic time series forecasts with autoregressive transformation models.

David Rügamer, Philipp F. M. Baumann, Thomas Kneib, Torsten Hothorn

Stat. Comput., April, 2023

Distributional regression modeling via generalized additive models for location, scale, and shape: An overview through a data set from learning analytics.

Fernando Marmolejo-Ramos, Mauricio Tejo, Marek Brabec, Jakub Kuzilek, Srecko Joksimovic, Vitomir Kovanovic, Jorge González, Thomas Kneib, Peter Bühlmann, Lucas Kook, Guillermo Briseño-Sánchez, Raydonal Ospina

WIREs Data Mining Knowl. Discov., 2023

TreeLearn: A Comprehensive Deep Learning Method for Segmenting Individual Trees from Forest Point Clouds.

Jonathan Henrich, Jan van Delden, Dominik Seidel, Thomas Kneib, Alexander S. Ecker

CoRR, 2023

Neural Additive Models for Location Scale and Shape: A Framework for Interpretable Neural Regression Beyond the Mean.

Anton Thielmann, René-Marcel Kruse, Thomas Kneib, Benjamin Säfken

CoRR, 2023

Coherence based Document Clustering.

Anton Thielmann, Christoph Weisser, Thomas Kneib, Benjamin Säfken

Proceedings of the 17th IEEE International Conference on Semantic Computing, 2023

2022

A non-stationary model for spatially dependent circular response data based on wrapped Gaussian processes.

Isa Marques, Thomas Kneib, Nadja Klein

Stat. Comput., 2022

Correcting for sample selection bias in Bayesian distributional regression models.

Paul F. V. Wiemann, Nadja Klein, Thomas Kneib

Comput. Stat. Data Anal., 2022

Twitmo: A Twitter Data Topic Modeling and Visualization Package for R.

Andreas Buchmüller, Gillian Kant, Christoph Weisser, Benjamin Säfken, Krisztina Kis-Katos, Thomas Kneib

CoRR, 2022

Distributional Gradient Boosting Machines.

Alexander März, Thomas Kneib

CoRR, 2022

Privacy Estimation on Twitter: Modelling the Effect of Latent Topics on Privacy by Integrating XGBoost, Topic and Generalized Additive Models.

Arne Tillmann, Lindrit Kqiku, Delphine Reinhardt, Christoph Weisser, Benjamin Säfken, Thomas Kneib

Proceedings of the IEEE Smartworld, 2022

2021

Conditional Model Selection in Mixed-Effects Models with cAIC4.

Benjamin Säfken, David Rügamer, Thomas Kneib, Sonja Greven

J. Stat. Softw., 2021

AuDoLab: Automatic document labelling and classification for extremely unbalanced data.

Arne Tillmann, Anton Thielmann, Gillian Kant, Christoph Weisser, Benjamin Säfken, Alexander Silbersdorff, Thomas Kneib

J. Open Source Softw., 2021

Transforming Autoregression: Interpretable and Expressive Time Series Forecast.

David Rügamer, Philipp F. M. Baumann, Thomas Kneib, Torsten Hothorn

CoRR, 2021

Identifying Topical Shifts in Twitter Streams: An Integration of Non-negative Matrix Factorisation, Sentiment Analysis and Structural Break Models for Large Scale Data.

Mattias Luber, Christoph Weisser, Benjamin Säfken, Alexander Silbersdorff, Thomas Kneib, Krisztina Kis-Katos

Proceedings of the Disinformation in Open Online Media, 2021

2020

Generalised joint regression for count data: a penalty extension for competitive settings.

Hendrik van der Wurp, Andreas Groll, Thomas Kneib, Giampiero Marra, Rosalba Radice

Stat. Comput., 2020

Noncrossing structured additive multiple-output Bayesian quantile regression models.

Bruno Santos, Thomas Kneib

Stat. Comput., 2020

Towards a Taxonomy of Data Heterogeneity.

Jan Röder, Jan Muntermann, Thomas Kneib

Proceedings of the Entwicklungen, 2020

2019

Generalized additive models with flexible response functions.

Elmar Spiegel, Thomas Kneib, Fabian Otto-Sobotka

Stat. Comput., 2019

Multivariate effect priors in bivariate semiparametric recursive Gaussian models.

Hauke Thaden, Nadja Klein, Thomas Kneib

Comput. Stat. Data Anal., 2019

LASSO-type penalization in the framework of generalized additive models for location, scale and shape.

Andreas Groll, Julien Hambuckers, Thomas Kneib, Nikolaus Umlauf

Comput. Stat. Data Anal., 2019

2018

Flexible estimation of time-varying effects for frequently purchased retail goods: a modeling approach based on household panel data.

Bernhard Baumgartner, Daniel Guhl, Thomas Kneib, Winfried J. Steiner

OR Spectr., 2018

Studying the occurrence and burnt area of wildfires using zero-one-inflated structured additive beta regression.

Laura Ríos-Pena, Thomas Kneib, Carmen Cadarso-Suárez, Nadja Klein, Manuel Marey-Pérez

Environ. Model. Softw., 2018

2017

Bayesian regularisation in geoadditive expectile regression.

Elisabeth Waldmann, Fabian Sobotka, Thomas Kneib

Stat. Comput., 2017

Markov-switching generalized additive models.

Roland Langrock, Thomas Kneib, Richard Glennie, Théo Michelot

Stat. Comput., 2017

Pathway-Based Kernel Boosting for the Analysis of Genome-Wide Association Studies.

Stefanie Friedrichs, Juliane Manitz, Patricia Burger, Christopher I. Amos, Angela Risch, Jenny Chang-Claude, Heinz-Erich Wichmann, Thomas Kneib, Heike Bickeböller, Benjamin Hofner

Comput. Math. Methods Medicine, 2017

2016

Simultaneous inference in structured additive conditional copula regression models: a unifying Bayesian approach.

Nadja Klein, Thomas Kneib

Stat. Comput., 2016

A unified framework of constrained regression.

Benjamin Hofner, Thomas Kneib, Torsten Hothorn

Stat. Comput., 2016

2015

Variational approximations in geoadditive latent Gaussian regression: mean and quantile regression.

Elisabeth Waldmann, Thomas Kneib

Stat. Comput., 2015

Fast smoothing parameter separation in multidimensional generalized P-splines: the SAP algorithm.

María Xosé Rodríguez-Álvarez, Dae-Jin Lee, Thomas Kneib, María Durbán, Paul H. C. Eilers

Stat. Comput., 2015

Semiparametric stochastic volatility modelling using penalized splines.

Roland Langrock, Théo Michelot, Alexander Sohn, Thomas Kneib

Comput. Stat., 2015

2014

Multilevel structured additive regression.

Stefan Lang, Nikolaus Umlauf, Peter Wechselberger, Kenneth Harttgen, Thomas Kneib

Stat. Comput., 2014

2013

On confidence intervals for semiparametric expectile regression.

Fabian Sobotka, Göran Kauermann, Linda Schulze Waltrup, Thomas Kneib

Stat. Comput., 2013

Variable selection and model choice in structured survival models.

Benjamin Hofner, Torsten Hothorn, Thomas Kneib

Comput. Stat., 2013

2012

Geoadditive expectile regression.

Fabian Sobotka, Thomas Kneib

Comput. Stat. Data Anal., 2012

2010

Bayesian regularisation in structured additive regression: a unifying perspective on shrinkage, smoothing and predictor selection.

Ludwig Fahrmeir, Thomas Kneib, Susanne Konrath

Stat. Comput., 2010

Model-based Boosting 2.0.

Torsten Hothorn, Peter Bühlmann, Thomas Kneib, Matthias Schmid, Benjamin Hofner

J. Mach. Learn. Res., 2010

2009

Locally adaptive Bayesian P-splines with a Normal-Exponential-Gamma prior.

Fabian Scheipl, Thomas Kneib

Comput. Stat. Data Anal., 2009

2008

Conditional variable importance for random forests.

Carolin Strobl, Anne-Laure Boulesteix, Thomas Kneib, Thomas Augustin, Achim Zeileis

BMC Bioinform., 2008

2006

Mixed model-based inference in geoadditive hazard regression for interval-censored survival times.

Thomas Kneib

Comput. Stat. Data Anal., 2006