Particle Swarm CMA Evolution Strategy for the optimization of multi-funnel landscapes. - Christian L. Müller; Benedikt Baumgartner; Ivo F. Sbalzarini (IEEE Congress on Evolutionary Computation, 2009)

pCMALib: a parallel fortran 90 library for the evolution strategy with covariance matrix adaptation. - Christian L. Müller; Benedikt Baumgartner; Georg Ofenbeck; Birte Schrader; Ivo F. Sbalzarini (GECCO, 2009)

A Tunable Real-world Multi-funnel Benchmark Problem for Evolutionary Optimization - And Why Parallel Island Models Might Remedy the Failure of CMA-ES on It. - Christian L. Müller; Ivo F. Sbalzarini (IJCCI, 2009)

Gaussian Adaptation as a unifying framework for continuous black-box optimization and adaptive Monte Carlo sampling. - Christian L. Müller; Ivo F. Sbalzarini (IEEE Congress on Evolutionary Computation, 2010)

Exploring the common concepts of adaptive MCMC and Covariance Matrix Adaptation schemes. - Christian L. Müller (Theory of Evolutionary Algorithms, 2010)

Gaussian Adaptation Revisited - An Entropic View on Covariance Matrix Adaptation. - Christian L. Müller; Ivo F. Sbalzarini (EvoApplications (1), 2010)

Black-box Landscapes: Characterization, Optimization, Sampling, and Application to Geometric Configuration Problems. - Christian L. Müller (2010)

Global Characterization of the CEC 2005 Fitness Landscapes Using Fitness-Distance Analysis. - Christian L. Müller; Ivo F. Sbalzarini (EvoApplications (1), 2011)

Global parameter identification of stochastic reaction networks from single trajectories - Christian L. Müller; Rajesh Ramaswamy; Ivo F. Sbalzarini (CoRR, 2011)

On Spectral Invariance of Randomized Hessian and Covariance Matrix Adaptation Schemes. - Sebastian U. Stich; Christian L. Müller (PPSN (1), 2012)

Energy Landscapes of Atomic Clusters as Black Box Optimization Benchmarks. - Christian L. Müller; Ivo F. Sbalzarini (Evol. Comput., 2012)

Optimization of Convex Functions with Random Pursuit. - Sebastian U. Stich; Christian L. Müller; Bernd Gärtner (SIAM J. Optim., 2013)

Don't Fall for Tuning Parameters: Tuning-Free Variable Selection in High Dimensions With the TREX. - Johannes Lederer; Christian L. Müller (AAAI, 2015)

Sparse and Compositionally Robust Inference of Microbial Ecological Networks. - Zachary D. Kurtz; Christian L. Müller; Emily R. Miraldi; Dan R. Littman; Martin J. Blaser; Richard A. Bonneau (PLoS Comput. Biol., 2015)

Non-convex Global Minimization and False Discovery Rate Control for the TREX. - Jacob Bien; Irina Gaynanova; Johannes Lederer; Christian L. Müller (CoRR, 2016)

Variable metric random pursuit. - Sebastian U. Stich; Christian L. Müller; Bernd Gärtner (Math. Program., 2016)

Fused Regression for Multi-source Gene Regulatory Network Inference. - Kari Y. Lam; Zachary M. Westrick; Christian L. Müller; Lionel A. Christiaen; Richard Bonneau (PLoS Comput. Biol., 2016)

4C-ker: A Method to Reproducibly Identify Genome-Wide Interactions Captured by 4C-Seq Experiments. - Ramya Raviram; Pedro P. Rocha; Christian L. Müller; Emily R. Miraldi; Sana Badri; Yi Fu; Emily Swanzey; Charlotte Proudhon; Valentina Snetkova; Richard Bonneau; Jane A. Skok (PLoS Comput. Biol., 2016)

Identifying direct contacts between protein complex subunits from their conditional dependence in proteomics datasets. - Kevin Drew; Christian L. Müller; Richard Bonneau; Edward M. Marcotte (PLoS Comput. Biol., 2017)

Temporal probabilistic modeling of bacterial compositions derived from 16S rRNA sequencing. - Tarmo Äijö; Christian L. Müller; Richard Bonneau (Bioinform., 2018)

Stability selection enables robust learning of partial differential equations from limited noisy data. - Suryanarayana Maddu; Bevan L. Cheeseman; Ivo F. Sbalzarini; Christian L. Müller (CoRR, 2019)

Learning physically consistent mathematical models from data using group sparsity. - Suryanarayana Maddu; Bevan L. Cheeseman; Christian L. Müller; Ivo F. Sbalzarini (CoRR, 2020)

NetCoMi: network construction and comparison for microbiome data in R. - Stefanie Peschel; Christian L. Müller; Erika von Mutius; Anne-Laure Boulesteix; Martin Depner (Briefings Bioinform., 2021)

STENCIL-NET: Data-driven solution-adaptive discretization of partial differential equations. - Suryanarayana Maddu; Dominik Sturm; Bevan L. Cheeseman; Christian L. Müller; Ivo F. Sbalzarini (CoRR, 2021)

deepregression: a Flexible Neural Network Framework for Semi-Structured Deep Distributional Regression. - David Rügamer; Ruolin Shen; Christina Bukas; Lisa Barros de Andrade e Sousa; Dominik Thalmeier; Nadja Klein; Chris Kolb; Florian Pfisterer; Philipp Kopper; Bernd Bischl; Christian L. Müller (CoRR, 2021)

A causal view on compositional data. - Elisabeth Ailer; Christian L. Müller; Niki Kilbertus (CoRR, 2021)

Objective hearing threshold identification from auditory brainstem response measurements using supervised and self-supervised approaches. - Dominik Thalmeier; Gregor Miller; Elida Schneltzer; Anja Hurt; Martin Hrabé de Angelis; Lore Becker; Christian L. Müller; Holger Maier (CoRR, 2021)

Fast Computation of Latent Correlations. - Grace Yoon; Christian L. Müller; Irina Gaynanova (J. Comput. Graph. Stat., 2021)

latentcor: An R Package for estimating latent correlations from mixed data types. - Mingze Huang; Christian L. Müller; Irina Gaynanova (J. Open Source Softw., 2021)

c-lasso - a Python package for constrained sparse and robust regression and classification. - Léo Simpson; Patrick L. Combettes; Christian L. Müller (J. Open Source Softw., 2021)

Factorized Structured Regression for Large-Scale Varying Coefficient Models. - David Rügamer; Andreas Bender 001; Simon Wiegrebe; Daniel Racek; Bernd Bischl; Christian L. Müller; Clemens Stachl (ECML/PKDD (5), 2022)

Robust regression with compositional covariates. - Aditya Mishra; Christian L. Müller (Comput. Stat. Data Anal., 2022)

Inverse Dirichlet weighting enables reliable training of physics informed neural networks. - Suryanarayana Maddu; Dominik Sturm; Christian L. Müller; Ivo F. Sbalzarini (Mach. Learn. Sci. Technol., 2022)

A randomization-based causal inference framework for uncovering environmental exposure effects on human gut microbiota. - Alice J. Sommer; Annette Peters; Martina Rommel; Josef Cyrys; Harald Grallert; Dirk Haller; Christian L. Müller; Marie-Abèle C. Bind (PLoS Comput. Biol., 2022)

Smoothing the Edges: A General Framework for Smooth Optimization in Sparse Regularization using Hadamard Overparametrization. - Chris Kolb; Christian L. Müller; Bernd Bischl; David Rügamer (CoRR, 2023)

deepregression: A Flexible Neural Network Framework for Semi-Structured Deep Distributional Regression. - David Rügamer; Chris Kolb; Cornelius Fritz; Florian Pfisterer; Philipp Kopper; Bernd Bischl; Ruolin Shen; Christina Bukas; Lisa Barros de Andrade e Sousa; Dominik Thalmeier; Philipp F. M. Baumann; Lucas Kook; et al. (J. Stat. Softw., 2023)

Over-optimism in unsupervised microbiome analysis: Insights from network learning and clustering. - Theresa Ullmann; Stefanie Peschel; Philipp F. M. Baumann; Christian L. Müller; Anne-Laure Boulesteix (PLoS Comput. Biol., 2023)