Articles with public access mandates - Joachim M. BuhmannLearn more
Not available anywhere: 6
Learning the compositional nature of visual object categories for recognition
B Ommer, J Buhmann
IEEE Transactions on Pattern Analysis and Machine Intelligence 32 (3), 501-516, 2009
Mandates: Swiss National Science Foundation
Classification of brain MRI with big data and deep 3D convolutional neural networks
V Wegmayr, S Aitharaju, J Buhmann
Medical Imaging 2018: Computer-Aided Diagnosis 10575, 406-412, 2018
Mandates: US Department of Defense, US National Institutes of Health, Canadian …
On the information and representation of non-Euclidean pairwise data
J Laub, V Roth, JM Buhmann, KR Muller
Pattern Recognition 39 (10), 1815-1826, 2006
Mandates: German Research Foundation
Stable Bayesian Parameter Estimation for Biological Dynamical Systems
AG Busetto, JM Buhmann
Computational Science and Engineering, 2009. CSE'09. International …, 2009
Mandates: Swiss National Science Foundation
Pipeline validation for connectivity-based cortex parcellation
NS Gorbach, M Tittgemeyer, JM Buhmann
NeuroImage 181, 219-234, 2018
Mandates: German Research Foundation
Computational Design of Informative Experiments in Systems Biology
AG Busetto, M Sunnåker, JM Buhmann
A Systems Theoretic Approach to Systems and Synthetic Biology I: Models and …, 2014
Mandates: Swiss National Science Foundation
Available somewhere: 69
Highly multiplexed imaging of tumor tissues with subcellular resolution by mass cytometry
C Giesen, HAO Wang, D Schapiro, N Zivanovic, A Jacobs, B Hattendorf, ...
Nature methods 11 (4), 417-422, 2014
Mandates: Swiss National Science Foundation, European Commission, Swiss Cancer League
Crowdsourcing the creation of image segmentation algorithms for connectomics
I Arganda-Carreras, SC Turaga, DR Berger, D Cireşan, A Giusti, ...
Frontiers in neuroanatomy 9, 152591, 2015
Mandates: US National Institutes of Health, Howard Hughes Medical Institute, Human …
Protein identification false discovery rates for very large proteomics data sets generated by tandem mass spectrometry
L Reiter, M Claassen, SP Schrimpf, M Jovanovic, A Schmidt, JM Buhmann, ...
Molecular & Cellular Proteomics 8 (11), 2405-2417, 2009
Mandates: Swiss National Science Foundation, US National Institutes of Health
Ti-pooling: transformation-invariant pooling for feature learning in convolutional neural networks
D Laptev, N Savinov, JM Buhmann, M Pollefeys
Proceedings of the IEEE conference on computer vision and pattern …, 2016
Mandates: Swiss National Science Foundation
Guarantees for greedy maximization of non-submodular functions with applications
AA Bian, JM Buhmann, A Krause, S Tschiatschek
International conference on machine learning, 498-507, 2017
Mandates: European Commission
Cancer genetics-guided discovery of serum biomarker signatures for diagnosis and prognosis of prostate cancer
I Cima, R Schiess, P Wild, M Kaelin, P Schüffler, V Lange, P Picotti, ...
Proceedings of the National Academy of Sciences 108 (8), 3342, 2011
Mandates: Swiss National Science Foundation
Dissecting psychiatric spectrum disorders by generative embedding
KH Brodersen, L Deserno, F Schlagenhauf, Z Lin, WD Penny, ...
NeuroImage: Clinical 4, 98-111, 2014
Mandates: Wellcome Trust
Towards weakly supervised semantic segmentation by means of multiple instance and multitask learning
A Vezhnevets, JM Buhmann
2010 IEEE computer society conference on computer vision and pattern …, 2010
Mandates: Swiss National Science Foundation
Weakly supervised structured output learning for semantic segmentation
A Vezhnevets, V Ferrari, JM Buhmann
2012 IEEE conference on computer vision and pattern recognition, 845-852, 2012
Mandates: Swiss National Science Foundation
Weakly supervised semantic segmentation with a multi-image model
A Vezhnevets, V Ferrari, JM Buhmann
2011 international conference on computer vision, 643-650, 2011
Mandates: Swiss National Science Foundation
Guaranteed non-convex optimization: Submodular maximization over continuous domains
AA Bian, B Mirzasoleiman, J Buhmann, A Krause
Artificial Intelligence and Statistics, 111-120, 2017
Mandates: European Commission
Active learning for semantic segmentation with expected change
A Vezhnevets, JM Buhmann, V Ferrari
2012 IEEE conference on computer vision and pattern recognition, 3162-3169, 2012
Mandates: Swiss National Science Foundation
Regression DCM for fMRI
S Frässle, EI Lomakina, A Razi, KJ Friston, JM Buhmann, KE Stephan
NeuroImage 155, 406-421, 2017
Mandates: European Commission
Automatic human sleep stage scoring using deep neural networks
A Malafeev, D Laptev, S Bauer, X Omlin, A Wierzbicka, A Wichniak, ...
Frontiers in neuroscience 12, 781, 2018
Mandates: Swiss National Science Foundation
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