Christian L. Müller

Orcid: 0000-0002-3821-7083

Affiliations:
  • LMU Munich, Germany
  • New York University, Center for Genomics and Systems Biology, USA (former)
  • ETH Zurich, Institute of Theoretical Computer Science, Switzerland (former)


According to our database1, Christian L. Müller authored at least 37 papers between 2009 and 2023.

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Bibliography

2023
Over-optimism in unsupervised microbiome analysis: Insights from network learning and clustering.
PLoS Comput. Biol., January, 2023

deepregression: A Flexible Neural Network Framework for Semi-Structured Deep Distributional Regression.
J. Stat. Softw., 2023

Smoothing the Edges: A General Framework for Smooth Optimization in Sparse Regularization using Hadamard Overparametrization.
CoRR, 2023

2022
A randomization-based causal inference framework for uncovering environmental exposure effects on human gut microbiota.
PLoS Comput. Biol., 2022

Inverse Dirichlet weighting enables reliable training of physics informed neural networks.
Mach. Learn. Sci. Technol., 2022

Robust regression with compositional covariates.
Comput. Stat. Data Anal., 2022

Factorized Structured Regression for Large-Scale Varying Coefficient Models.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2022

2021
c-lasso - a Python package for constrained sparse and robust regression and classification.
J. Open Source Softw., 2021

latentcor: An R Package for estimating latent correlations from mixed data types.
J. Open Source Softw., 2021

Fast Computation of Latent Correlations.
J. Comput. Graph. Stat., 2021

Objective hearing threshold identification from auditory brainstem response measurements using supervised and self-supervised approaches.
CoRR, 2021

A causal view on compositional data.
CoRR, 2021

deepregression: a Flexible Neural Network Framework for Semi-Structured Deep Distributional Regression.
CoRR, 2021

STENCIL-NET: Data-driven solution-adaptive discretization of partial differential equations.
CoRR, 2021

NetCoMi: network construction and comparison for microbiome data in R.
Briefings Bioinform., 2021

2020
Learning physically consistent mathematical models from data using group sparsity.
CoRR, 2020

2019
Stability selection enables robust learning of partial differential equations from limited noisy data.
CoRR, 2019

2018
Temporal probabilistic modeling of bacterial compositions derived from 16S rRNA sequencing.
Bioinform., 2018

2017
Identifying direct contacts between protein complex subunits from their conditional dependence in proteomics datasets.
PLoS Comput. Biol., 2017

2016
4C-ker: A Method to Reproducibly Identify Genome-Wide Interactions Captured by 4C-Seq Experiments.
PLoS Comput. Biol., 2016

Fused Regression for Multi-source Gene Regulatory Network Inference.
PLoS Comput. Biol., 2016

Variable metric random pursuit.
Math. Program., 2016

Non-convex Global Minimization and False Discovery Rate Control for the TREX.
CoRR, 2016

2015
Sparse and Compositionally Robust Inference of Microbial Ecological Networks.
PLoS Comput. Biol., 2015

Don't Fall for Tuning Parameters: Tuning-Free Variable Selection in High Dimensions With the TREX.
Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

2013
Optimization of Convex Functions with Random Pursuit.
SIAM J. Optim., 2013

2012
Energy Landscapes of Atomic Clusters as Black Box Optimization Benchmarks.
Evol. Comput., 2012

On Spectral Invariance of Randomized Hessian and Covariance Matrix Adaptation Schemes.
Proceedings of the Parallel Problem Solving from Nature - PPSN XII, 2012

2011
Global parameter identification of stochastic reaction networks from single trajectories
CoRR, 2011

Global Characterization of the CEC 2005 Fitness Landscapes Using Fitness-Distance Analysis.
Proceedings of the Applications of Evolutionary Computation, 2011

2010
Black-box Landscapes: Characterization, Optimization, Sampling, and Application to Geometric Configuration Problems.
PhD thesis, 2010

Gaussian Adaptation Revisited - An Entropic View on Covariance Matrix Adaptation.
Proceedings of the Applications of Evolutionary Computation, 2010

Exploring the common concepts of adaptive MCMC and Covariance Matrix Adaptation schemes.
Proceedings of the Theory of Evolutionary Algorithms, 05.09. - 10.09.2010, 2010

Gaussian Adaptation as a unifying framework for continuous black-box optimization and adaptive Monte Carlo sampling.
Proceedings of the IEEE Congress on Evolutionary Computation, 2010

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.
Proceedings of the IJCCI 2009, 2009

pCMALib: a parallel fortran 90 library for the evolution strategy with covariance matrix adaptation.
Proceedings of the Genetic and Evolutionary Computation Conference, 2009

Particle Swarm CMA Evolution Strategy for the optimization of multi-funnel landscapes.
Proceedings of the IEEE Congress on Evolutionary Computation, 2009


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