| Semi-supervised kernel canonical correlation analysis with application to human fMRI MB Blaschko, JA Shelton, A Bartels, CH Lampert, A Gretton Pattern Recognition Letters 32 (11), 1572-1583, 2011 | 51 | 2011 |
| A truncated EM approach for spike-and-slab sparse coding AS Sheikh, JA Shelton, J Lücke The Journal of Machine Learning Research 15 (1), 2653-2687, 2014 | 47 | 2014 |
| Select and sample-a model of efficient neural inference and learning J Shelton, A Sheikh, P Berkes, J Bornschein, J Lücke Advances in neural information processing systems 24, 2011 | 26 | 2011 |
| GP-select: Accelerating EM using adaptive subspace preselection JA Shelton, J Gasthaus, Z Dai, J Lücke, A Gretton Neural Computation 29 (8), 2177-2202, 2017 | 23 | 2017 |
| Augmenting feature-driven fMRI analyses: Semi-supervised learning and resting state activity A Bartels, M Blaschko, J Shelton Advances in neural information processing systems 22, 2009 | 19 | 2009 |
| Instance segmentation of fallen trees in aerial color infrared imagery using active multi-contour evolution with fully convolutional network-based intensity priors P Polewski, J Shelton, W Yao, M Heurich ISPRS Journal of Photogrammetry and Remote Sensing 178, 297-313, 2021 | 17 | 2021 |
| Nonlinear spike-and-slab sparse coding for interpretable image encoding JA Shelton, AS Sheikh, J Bornschein, P Sterne, J Luecke PLoS One 10 (5), e0124088, 2015 | 16 | 2015 |
| Why MCA? Nonlinear sparse coding with spike-and-slab prior for neurally plausible image encoding P Sterne, J Bornschein, A Sheikh, J Lücke, J Shelton Advances in neural information processing systems 25, 2012 | 9 | 2012 |
| Segmentation of single standing dead trees in high-resolution aerial imagery with generative adversarial network-based shape priors P Polewski, J Shelton, W Yao, M Heurich The International Archives of the Photogrammetry, Remote Sensing and Spatial …, 2020 | 5 | 2020 |
| Challenges of developing engineering students’ writing through peer assessment T McConlogue, J Mueller, J Shelton The Higher Education Academy Engineering Subject Centre, EE, 2010 | 5 | 2010 |
| Semi-supervised subspace analysis of human functional magnetic resonance imaging data J Shelton, M Blaschko, A Bartels Max Planck Institute for Biological Cybernetics, 2009 | 5 | 2009 |
| U-net for learning and inference of dense representation of multiple air pollutants from satellite imagery J Shelton, P Polewski, W Yao Proceedings of the 10th International Conference on Climate Informatics, 128-133, 2020 | 3 | 2020 |
| Similarities in resting state and feature-driven activity: Non-parametric evaluation of human fMRI JA Shelton, MB Blaschko, A Gretton, J Müller, E Fischer, A Bartels NIPS 2010 Workshop on Learning and Planning from Batch Time Series Data, 1-2, 2010 | 3 | 2010 |
| Semi-supervised subspace learning and application to human functional magnetic brain resonance imaging data J Shelton Eberhard Karls Universität Tübingen, Germany, 2010 | 2 | 2010 |
| A hybrid convolutional neural network/active contour approach to segmenting dead trees in aerial imagery JA Shelton, P Polewski, W Yao, M Heurich arXiv preprint arXiv:2112.02725, 2021 | 1 | 2021 |
| Decomposing Antarctic Sub-shelf Melt Variability using Generalized Clustering with Kernel Embeddings J Shelton, A Robel, MJ Hoffman, SF Price AGU23, 2023 | | 2023 |
| Generating Antarctic Sub-shelf Melt Using Recurrent Neural Network-based Generative Adversarial Networks on Spatiotemporal Pixel Clusters J Shelton, A Robel, MJ Hoffman, SF Price AGU Fall Meeting Abstracts 2022, C52C-0372, 2022 | | 2022 |
| In the Danger Zone: U-Net Driven Quantile Regression can Predict High-risk SARS-CoV-2 Regions via Pollutant Particulate Matter and Satellite Imagery J Shelton, P Polewski, W Yao arXiv preprint arXiv:2105.02406, 2021 | | 2021 |
| Large-scale approximate EM-style learning and inference in generative graphical models for sparse coding JA Shelton Dissertation, Berlin, Technische Universität Berlin, 2018, 2018 | | 2018 |
| Augmentation of fMRI data analysis using resting state activity and Semi-supervised Canonical Correlation Analysis JA Shelton, M Blaschko, A Bartels NIPS 2010 Women in Machine Learning Workshop (WiML 2010), 2010 | | 2010 |
Jorg LuckeProfessor of Machine Learning, University of Oldenburg, Germany.Verified email at uni-oldenburg.de
