Comparative evaluation of reverse engineering gene regulatory networks with relevance networks, graphical gaussian models and bayesian networks. - Adriano Velasque Werhli; Marco Grzegorczyk; Dirk Husmeier (Bioinform., 2006)

Modelling non-stationary gene regulatory processes with a non-homogeneous Bayesian network and the allocation sampler. - Marco Grzegorczyk; Dirk Husmeier; Kieron D. Edwards; Peter Ghazal; Andrew J. Millar (Bioinform., 2008)

Improving the structure MCMC sampler for Bayesian networks by introducing a new edge reversal move. - Marco Grzegorczyk; Dirk Husmeier (Mach. Learn., 2008)

Non-stationary continuous dynamic Bayesian networks. - Marco Grzegorczyk; Dirk Husmeier (NIPS, 2009)

Avoiding Spurious Feedback Loops in the Reconstruction of Gene Regulatory Networks with Dynamic Bayesian Networks. - Marco Grzegorczyk; Dirk Husmeier (PRIB, 2009)

Modelling Nonstationary Gene Regulatory Processes. - Marco Grzegorczyk; Dirk Husmeier; Jörg Rahnenführer (Adv. Bioinformatics, 2010)

Improvements in the reconstruction of time-varying gene regulatory networks: dynamic programming and regularization by information sharing among genes. - Marco Grzegorczyk; Dirk Husmeier (Bioinform., 2011)

Modelling non-stationary dynamic gene regulatory processes with the BGM model. - Marco Grzegorczyk; Dirk Husmeier; Jörg Rahnenführer (Comput. Stat., 2011)

Non-homogeneous dynamic Bayesian networks for continuous data. - Marco Grzegorczyk; Dirk Husmeier (Mach. Learn., 2011)

Bayesian regularization of non-homogeneous dynamic Bayesian networks by globally coupling interaction parameters. - Marco Grzegorczyk; Dirk Husmeier (AISTATS, 2012)

Regularization of non-homogeneous dynamic Bayesian networks with global information-coupling based on hierarchical Bayesian models. - Marco Grzegorczyk; Dirk Husmeier (Mach. Learn., 2013)

Inference of Circadian Regulatory Networks. - Marco Grzegorczyk; Andrej Aderhold; V. Anne Smith; Dirk Husmeier (IWBBIO, 2014)

A non-homogeneous dynamic Bayesian network with a hidden Markov model dependency structure among the temporal data points. - Marco Grzegorczyk (Mach. Learn., 2016)

Targeting Bayes factors with direct-path non-equilibrium thermodynamic integration. - Marco Grzegorczyk; Andrej Aderhold; Dirk Husmeier (Comput. Stat., 2017)

Comparative evaluation of various frequentist and Bayesian non-homogeneous Poisson counting models. - Marco Grzegorczyk; Mahdi Shafiee Kamalabad (Comput. Stat., 2017)

Approximate Bayesian inference in semi-mechanistic models. - Andrej Aderhold; Dirk Husmeier; Marco Grzegorczyk (Stat. Comput., 2017)

A New Partially Segment-Wise Coupled Piece-Wise Linear Regression Model for Statistical Network Structure Inference. - Mahdi Shafiee Kamalabad; Marco Grzegorczyk (CIBB, 2018)

Exact hypothesis testing for shrinkage-based Gaussian graphical models. - Victor Bernal; Rainer Bischoff 003; Victor Guryev; Marco Grzegorczyk; Peter Horvatovich (Bioinform., 2019)

Partially non-homogeneous dynamic Bayesian networks based on Bayesian regression models with partitioned design matrices. - Mahdi Shafiee Kamalabad; Alexander Martin Heberle; Kathrin Thedieck; Marco Grzegorczyk (Bioinform., 2019)

A new Bayesian multivariate exponentially weighted moving average control chart for phase II monitoring of multivariate multiple linear profiles. - Ahmad Ahmadi Yazdi; Ali Zeinal Hamadani; Amirhossein Amiri; Marco Grzegorczyk (Qual. Reliab. Eng. Int., 2019)

Non-homogeneous dynamic Bayesian networks with edge-wise sequentially coupled parameters. - Mahdi Shafiee Kamalabad; Marco Grzegorczyk (Bioinform., 2020)

The 'un-shrunk' partial correlation in Gaussian graphical models. - Victor Bernal; Rainer Bischoff 003; Peter Horvatovich; Victor Guryev; Marco Grzegorczyk (BMC Bioinform., 2021)

A new Bayesian piecewise linear regression model for dynamic network reconstruction. - Mahdi Shafiee Kamalabad; Marco Grzegorczyk (BMC Bioinform., 2021)

GeneNetTools: tests for Gaussian graphical models with shrinkage. - Victor Bernal; Venustiano Soancatl-Aguilar; Jonas Bulthuis; Victor Guryev; Peter Horvatovich; Marco Grzegorczyk (Bioinform., 2022)

Model averaging for sparse seemingly unrelated regression using Bayesian networks among the errors. - Abdul Salam; Marco Grzegorczyk (Comput. Stat., 2023)

Being Bayesian about learning Gaussian Bayesian networks from incomplete data. - Marco Grzegorczyk (Int. J. Approx. Reason., 2023)

Scalable inference of cell differentiation networks in gene therapy clonal tracking studies of haematopoiesis. - Luca Del Core; Danilo Pellin; Ernst C. Wit; Marco Grzegorczyk (Bioinform., 2023)

A mixed-effects stochastic model reveals clonal dominance in gene therapy safety studies. - Luca Del Core; Danilo Pellin; Ernst C. Wit; Marco Grzegorczyk (BMC Bioinform., 2023)

Contextual Online Imitation Learning (COIL): Using Guide Policies in Reinforcement Learning. - Alexander Hill; Marc Groefsema; Matthia Sabatelli; Raffaella Carloni; Marco Grzegorczyk (ICAART (3), 2024)

Being Bayesian about learning Bayesian networks from ordinal data. - Marco Grzegorczyk (Int. J. Approx. Reason., 2024)

Being Bayesian about learning Bayesian networks from hybrid data. - Marco Grzegorczyk (Int. J. Approx. Reason., 2025)