Andreas Christian Mueller
TitleCited byYear
Evaluation of pooling operations in convolutional architectures for object recognition
D Scherer, A Müller, S Behnke
Artificial Neural Networks–ICANN 2010, 92-101, 2010
8932010
API design for machine learning software: experiences from the scikit-learn project
L Buitinck, G Louppe, M Blondel, F Pedregosa, A Mueller, O Grisel, ...
arXiv preprint arXiv:1309.0238, 2013
6542013
Machine learning for neuroimaging with scikit-learn
A Abraham, F Pedregosa, M Eickenberg, P Gervais, A Mueller, J Kossaifi, ...
Frontiers in neuroinformatics 8, 14, 2014
3702014
Introduction to machine learning with Python: a guide for data scientists
AC Müller, S Guido
" O'Reilly Media, Inc.", 2016
2182016
Learning depth-sensitive conditional random fields for semantic segmentation of RGB-D images
AC Müller, S Behnke
2014 IEEE International Conference on Robotics and Automation (ICRA), 6232-6237, 2014
722014
Pystruct: learning structured prediction in python
AC Müller, S Behnke
The Journal of Machine Learning Research 15 (1), 2055-2060, 2014
642014
Investigating convergence of restricted boltzmann machine learning
H Schulz, A Müller, S Behnke
NIPS 2010 Workshop on Deep Learning and Unsupervised Feature Learning, 2010
452010
Scikit-learn: Machine learning without learning the machinery
G Varoquaux, L Buitinck, G Louppe, O Grisel, F Pedregosa, A Mueller
GetMobile: Mobile Computing and Communications 19 (1), 29-33, 2015
372015
Information Theoretic Clustering Using Minimum Spanning Trees
A Müller, S Nowozin, C Lampert
Pattern Recognition, 205-215, 2012
332012
Using machine learning to explore the long-term evolution of GRS 1915+ 105
D Huppenkothen, LM Heil, DW Hogg, A Mueller
Monthly Notices of the Royal Astronomical Society 466 (2), 2364-2377, 2016
112016
Exploiting local structure in Boltzmann machines
H Schulz, A Müller, S Behnke
Neurocomputing 74 (9), 1411-1417, 2011
82011
Einführung in Machine learning mit Python: Praxiswissen data science
AC Müller, S Guido
O'Reilly, 2017
72017
Methods for learning structured prediction in semantic segmentation of natural images
A Müller
Universitäts-und Landesbibliothek Bonn, 2014
72014
Multi-instance methods for partially supervised image segmentation
A Müller, S Behnke
IAPR International Workshop on Partially Supervised Learning, 110-119, 2011
62011
Learning a Loopy Model For Semantic Segmentation Exactly
AC Müller, S Behnke
arXiv preprint arXiv:1309.4061, 2013
52013
Topological features in locally connected RBMs
A Müller, H Schulz, S Behnke
The 2010 International Joint Conference on Neural Networks (IJCNN), 1-6, 2010
52010
Exploiting local structure in stacked Boltzmann machines.
H Schulz, AC Müller, S Behnke
ESANN, 2010
32010
Meta learning for defaults: Symbolic defaults
JN van Rijn, F Pfisterer, J Thomas, A Muller, B Bischl, J Vanschoren
Neural Information Processing Workshop on Meta-Learning, 2018
12018
Learning Multiple Defaults for Machine Learning Algorithms
F Pfisterer, JN van Rijn, P Probst, A Müller, B Bischl
arXiv preprint arXiv:1811.09409, 2018
12018
Computational derivation of a molecular framework for hair follicle biology from disease genes
RK Severin, X Li, K Qian, AC Mueller, L Petukhova
Scientific reports 7 (1), 16303, 2017
12017
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Articles 1–20