Christian L. Müller | DeepAI

DeepAI AI Chat

Featured Co-authors

Bernd Bischl
93 publications
David Rügamer
37 publications
Nadja Klein
35 publications
Jacob Bien
32 publications
Niki Kilbertus
25 publications
Irina Gaynanova
25 publications
Ivo F. Sbalzarini
23 publications
Florian Pfisterer
22 publications
Andreas Bender
19 publications
Suryanarayana Maddu
6 publications
Clemens Stachl
6 publications

∙ 07/07/2023

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

This paper introduces a smooth method for (structured) sparsity in ℓ_q a...

0 Chris Kolb, et al. ∙

∙ 05/25/2022

Factorized Structured Regression for Large-Scale Varying Coefficient Models

Recommender Systems (RS) pervade many aspects of our everyday digital li...

0 David Rügamer, et al. ∙

∙ 12/16/2021

Objective hearing threshold identification from auditory brainstem response measurements using supervised and self-supervised approaches

Hearing loss is a major health problem and psychological burden in human...

0 Dominik Thalmeier, et al. ∙

∙ 11/16/2021

Ocean Mover's Distance: Using Optimal Transport for Analyzing Oceanographic Data

Modern ocean datasets are large, multi-dimensional, and inherently spati...

0 Sangwon Hyun, et al. ∙

∙ 10/20/2021

GGLasso – a Python package for General Graphical Lasso computation

We introduce GGLasso, a Python package for solving General Graphical Las...

0 Fabian Schaipp, et al. ∙

∙ 08/20/2021

latentcor: An R Package for estimating latent correlations from mixed data types

We present `latentcor`, an R package for correlation estimation from dat...

0 Mingze Huang, et al. ∙

∙ 06/21/2021

A causal view on compositional data

Many scientific datasets are compositional in nature. Important examples...

0 Elisabeth Ailer, et al. ∙

∙ 04/06/2021

deepregression: a Flexible Neural Network Framework for Semi-Structured Deep Distributional Regression

This paper describes the implementation of semi-structured deep distribu...

0 David Rügamer, et al. ∙

∙ 01/15/2021

STENCIL-NET: Data-driven solution-adaptive discretization of partial differential equations

Numerical methods for approximately solving partial differential equatio...

14 Suryanarayana Maddu, et al. ∙

∙ 12/11/2020

Learning physically consistent mathematical models from data using group sparsity

We propose a statistical learning framework based on group-sparse regres...

16 Suryanarayana Maddu, et al. ∙

∙ 11/02/2020

c-lasso – a Python package for constrained sparse and robust regression and classification

We introduce c-lasso, a Python package that enables sparse and robust li...

0 Léo Simpson, et al. ∙

∙ 06/24/2020

Fast computation of latent correlations

Latent Gaussian copula models provide a powerful means to perform multi-...

0 Grace Yoon, et al. ∙

∙ 07/17/2019

Stability selection enables robust learning of partial differential equations from limited noisy data

We present a statistical learning framework for robust identification of...

0 Suryanarayana Maddu, et al. ∙

∙ 03/04/2019

Regression models for compositional data: General log-contrast formulations, proximal optimization, and microbiome data applications

Compositional data sets are ubiquitous in science, including geology, ec...

0 Patrick L. Combettes, et al. ∙

∙ 05/16/2018

Perspective Maximum Likelihood-Type Estimation via Proximal Decomposition

We introduce an optimization model for maximum likelihood-type estimatio...

0 Patrick L. Combettes, et al. ∙

Are you a researcher?
Expose your work
to one of the largest
A.I. communities in the world