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ORCIDChristian L. Müller
Person information
- affiliation: LMU Munich, Germany
- affiliation (former): New York University, Center for Genomics and Systems Biology, USA
- affiliation (former): ETH Zurich, Institute of Theoretical Computer Science, Switzerland
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2020 – today
- 2023
[j17]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, Nadja Klein, Christian L. Müller:
deepregression: A Flexible Neural Network Framework for Semi-Structured Deep Distributional Regression. J. Stat. Softw. 105(2) (2023)- [j16]Theresa Ullmann, Stefanie Peschel, Philipp F. M. Baumann, Christian L. Müller, Anne-Laure Boulesteix:
Over-optimism in unsupervised microbiome analysis: Insights from network learning and clustering. PLoS Comput. Biol. 19(1) (2023) - [i14]Chris Kolb, Christian L. Müller, Bernd Bischl, David Rügamer:
Smoothing the Edges: A General Framework for Smooth Optimization in Sparse Regularization using Hadamard Overparametrization. CoRR abs/2307.03571 (2023) - 2022
- [j15]Aditya Mishra, Christian L. Müller:
Robust regression with compositional covariates. Comput. Stat. Data Anal. 165: 107315 (2022) - [j14]Suryanarayana Maddu, Dominik Sturm, Christian L. Müller, Ivo F. Sbalzarini:
Inverse Dirichlet weighting enables reliable training of physics informed neural networks. Mach. Learn. Sci. Technol. 3(1): 15026 (2022) - [j13]Alice J. Sommer, Annette Peters, Martina Rommel, Josef Cyrys, Harald Grallert, Dirk Haller, Christian L. Müller, Marie-Abèle C. Bind:
A randomization-based causal inference framework for uncovering environmental exposure effects on human gut microbiota. PLoS Comput. Biol. 18(5) (2022) - [c9]David Rügamer, Andreas Bender, Simon Wiegrebe, Daniel Racek, Bernd Bischl, Christian L. Müller, Clemens Stachl:
Factorized Structured Regression for Large-Scale Varying Coefficient Models. ECML/PKDD (5) 2022: 20-35 - [i13]David Rügamer, Andreas Bender, Simon Wiegrebe, Daniel Racek, Bernd Bischl, Christian L. Müller, Clemens Stachl:
Factorized Structured Regression for Large-Scale Varying Coefficient Models. CoRR abs/2205.13080 (2022) - 2021
- [j12]Stefanie Peschel, Christian L. Müller, Erika von Mutius, Anne-Laure Boulesteix, Martin Depner:
NetCoMi: network construction and comparison for microbiome data in R. Briefings Bioinform. 22(4) (2021) - [j11]Grace Yoon, Christian L. Müller, Irina Gaynanova:
Fast Computation of Latent Correlations. J. Comput. Graph. Stat. 30(4): 1249-1256 (2021) - [j10]Léo Simpson, Patrick L. Combettes, Christian L. Müller:
c-lasso - a Python package for constrained sparse and robust regression and classification. J. Open Source Softw. 6(57): 2844 (2021) - [j9]Mingze Huang, Christian L. Müller, Irina Gaynanova:
latentcor: An R Package for estimating latent correlations from mixed data types. J. Open Source Softw. 6(65): 3634 (2021) - [i12]Suryanarayana Maddu, Dominik Sturm, Bevan L. Cheeseman, Christian L. Müller, Ivo F. Sbalzarini:
STENCIL-NET: Data-driven solution-adaptive discretization of partial differential equations. CoRR abs/2101.06182 (2021) - [i11]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:
deepregression: a Flexible Neural Network Framework for Semi-Structured Deep Distributional Regression. CoRR abs/2104.02705 (2021) - [i10]Elisabeth Ailer, Christian L. Müller, Niki Kilbertus:
A causal view on compositional data. CoRR abs/2106.11234 (2021) - [i9]Suryanarayana Maddu, Dominik Sturm, Christian L. Müller, Ivo F. Sbalzarini:
Inverse-Dirichlet Weighting Enables Reliable Training of Physics Informed Neural Networks. CoRR abs/2107.00940 (2021) - [i8]Dominik Thalmeier, Gregor Miller, Elida Schneltzer, Anja Hurt, Martin Hrabé de Angelis, Lore Becker, Christian L. Müller, Holger Maier:
Objective hearing threshold identification from auditory brainstem response measurements using supervised and self-supervised approaches. CoRR abs/2112.08961 (2021) - 2020
- [i7]Léo Simpson, Patrick L. Combettes, Christian L. Müller:
c-lasso - a Python package for constrained sparse and robust regression and classification. CoRR abs/2011.00898 (2020) - [i6]Suryanarayana Maddu, Bevan L. Cheeseman, Christian L. Müller, Ivo F. Sbalzarini:
Learning physically consistent mathematical models from data using group sparsity. CoRR abs/2012.06391 (2020)
2010 – 2019
- 2019
- [i5]Suryanarayana Maddu, Bevan L. Cheeseman, Ivo F. Sbalzarini, Christian L. Müller:
Stability selection enables robust learning of partial differential equations from limited noisy data. CoRR abs/1907.07810 (2019) - 2018
- [j8]Tarmo Äijö, Christian L. Müller, Richard Bonneau:
Temporal probabilistic modeling of bacterial compositions derived from 16S rRNA sequencing. Bioinform. 34(3): 372-380 (2018) - 2017
- [j7]Kevin Drew, Christian L. Müller, Richard Bonneau, Edward M. Marcotte:
Identifying direct contacts between protein complex subunits from their conditional dependence in proteomics datasets. PLoS Comput. Biol. 13(10) (2017) - 2016
- [j6]Sebastian U. Stich, Christian L. Müller, Bernd Gärtner:
Variable metric random pursuit. Math. Program. 156(1-2): 549-579 (2016) - [j5]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:
4C-ker: A Method to Reproducibly Identify Genome-Wide Interactions Captured by 4C-Seq Experiments. PLoS Comput. Biol. 12(3) (2016) - [j4]Kari Y. Lam, Zachary M. Westrick, Christian L. Müller, Lionel A. Christiaen, Richard Bonneau:
Fused Regression for Multi-source Gene Regulatory Network Inference. PLoS Comput. Biol. 12(12) (2016) - [i4]Jacob Bien, Irina Gaynanova, Johannes Lederer, Christian L. Müller:
Non-convex Global Minimization and False Discovery Rate Control for the TREX. CoRR abs/1604.06815 (2016) - 2015
- [j3]Zachary D. Kurtz, Christian L. Müller, Emily R. Miraldi, Dan R. Littman, Martin J. Blaser, Richard A. Bonneau:
Sparse and Compositionally Robust Inference of Microbial Ecological Networks. PLoS Comput. Biol. 11(5) (2015) - [c8]Johannes Lederer, Christian L. Müller:
Don't Fall for Tuning Parameters: Tuning-Free Variable Selection in High Dimensions With the TREX. AAAI 2015: 2729-2735 - 2013
- [j2]Sebastian U. Stich, Christian L. Müller, Bernd Gärtner:
Optimization of Convex Functions with Random Pursuit. SIAM J. Optim. 23(2): 1284-1309 (2013) - 2012
- [j1]Christian L. Müller, Ivo F. Sbalzarini:
Energy Landscapes of Atomic Clusters as Black Box Optimization Benchmarks. Evol. Comput. 20(4): 543-573 (2012) - [c7]Sebastian U. Stich, Christian L. Müller:
On Spectral Invariance of Randomized Hessian and Covariance Matrix Adaptation Schemes. PPSN (1) 2012: 448-457 - 2011
- [c6]Christian L. Müller, Ivo F. Sbalzarini:
Global Characterization of the CEC 2005 Fitness Landscapes Using Fitness-Distance Analysis. EvoApplications (1) 2011: 294-303 - [i3]Sebastian U. Stich, Christian L. Müller, Bernd Gärtner:
Optimization of Convex Functions with Random Pursuit. CoRR abs/1111.0194 (2011) - [i2]Christian L. Müller, Rajesh Ramaswamy, Ivo F. Sbalzarini:
Global parameter identification of stochastic reaction networks from single trajectories. CoRR abs/1111.4785 (2011) - 2010
- [b1]Christian L. Müller:
Black-box Landscapes: Characterization, Optimization, Sampling, and Application to Geometric Configuration Problems. ETH Zurich, Zürich, Switzerland, 2010 - [c5]Christian L. Müller, Ivo F. Sbalzarini:
Gaussian Adaptation as a unifying framework for continuous black-box optimization and adaptive Monte Carlo sampling. IEEE Congress on Evolutionary Computation 2010: 1-8 - [c4]Christian L. Müller, Ivo F. Sbalzarini:
Gaussian Adaptation Revisited - An Entropic View on Covariance Matrix Adaptation. EvoApplications (1) 2010: 432-441 - [i1]Christian L. Müller:
Exploring the common concepts of adaptive MCMC and Covariance Matrix Adaptation schemes. Theory of Evolutionary Algorithms 2010
2000 – 2009
- 2009
- [c3]Christian L. Müller, Benedikt Baumgartner, Ivo F. Sbalzarini:
Particle Swarm CMA Evolution Strategy for the optimization of multi-funnel landscapes. IEEE Congress on Evolutionary Computation 2009: 2685-2692 - [c2]Christian L. Müller, Benedikt Baumgartner, Georg Ofenbeck, Birte Schrader, Ivo F. Sbalzarini:
pCMALib: a parallel fortran 90 library for the evolution strategy with covariance matrix adaptation. GECCO 2009: 1411-1418 - [c1]Christian L. Müller, Ivo F. Sbalzarini:
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. IJCCI 2009: 248-253
Coauthor Index
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