Parametric nonlinear dimensionality reduction using kernel t-SNE A Gisbrecht, A Schulz, B Hammer Neurocomputing, 2015 | 275 | 2015 |
Counteracting electrode shifts in upper-limb prosthesis control via transfer learning C Prahm, A Schulz, B Paaßen, J Schoisswohl, E Kaniusas, G Dorffner, ... IEEE Transactions on Neural Systems and Rehabilitation Engineering 27 (5 …, 2019 | 52 | 2019 |
Transfer Learning for Rapid Re-calibration of a Myoelectric Prosthesis After Electrode Shift Cosima Prahm, B Paassen, A Schulz, B Hammer, O Aszmann Converging Clinical and Engineering Research on Neurorehabilitation II, 153-157, 2017 | 50* | 2017 |
Expectation maximization transfer learning and its application for bionic hand prostheses B Paaßen, A Schulz, J Hahne, B Hammer Neurocomputing 298, 122-133, 2018 | 33 | 2018 |
Deepview: Visualizing classification boundaries of deep neural networks as scatter plots using discriminative dimensionality reduction A Schulz, F Hinder, B Hammer (IJCAI 2020) Proceedings of the Twenty-Ninth International Conference on …, 2019 | 32 | 2019 |
Using discriminative dimensionality reduction to visualize classifiers A Schulz, A Gisbrecht, B Hammer Neural Processing Letters 42 (1), 27-54, 2015 | 32 | 2015 |
Tissue-and development-stage–specific mRNA and heterogeneous CNV signatures of human ribosomal proteins in normal and cancer samples A Panda, A Yadav, H Yeerna, A Singh, M Biehl, M Lux, A Schulz, T Klecha, ... Nucleic acids research 48 (13), 7079-7098, 2020 | 19 | 2020 |
Valid interpretation of feature relevance for linear data mappings B Fránay, D Hofmann, A Schulz, M Biehl, B Hammer Computational Intelligence and Data Mining (CIDM), 2014 IEEE Symposium on, 2014 | 16 | 2014 |
Using nonlinear dimensionality reduction to visualize classifiers. volume 7902 of IWANN (1) A Schulz, A Gisbrecht, B Hammer Springer, 2013 | 16 | 2013 |
Linear Supervised Transfer Learning for Generalized Matrix LVQ B Paaßen, A Schulz, B Hammer Proceedings of the Workshop New Challenges in Neural Computation 2016, 2016 | 13 | 2016 |
Evaluating metrics for bias in word embeddings S Schröder, A Schulz, P Kenneweg, R Feldhans, F Hinder, B Hammer arXiv preprint arXiv:2111.07864, 2021 | 12 | 2021 |
Inferring feature relevances from metric learning A Schulz, B Mokbel, M Biehl, B Hammer Computational Intelligence, 2015 IEEE Symposium Series on, 2015 | 12 | 2015 |
How to Visualize Large Data Sets? B Hammer, A Gisbrecht, A Schulz Advances in Self-Organizing Maps, 2013 | 11 | 2013 |
Abundance, classification and genetic potential of Thaumarchaeota in metagenomes of European agricultural soils: a meta-analysis J Nelkner, L Huang, TW Lin, A Schulz, B Osterholz, C Henke, J Blom, ... Environmental Microbiome 18 (1), 26, 2023 | 8 | 2023 |
Reservoir memory machines as neural computers B Paaßen, A Schulz, TC Stewart, B Hammer IEEE Transactions on Neural Networks and Learning Systems, 2021 | 5 | 2021 |
An EM transfer learning algorithm with applications in bionic hand prostheses B Paaßen, A Schulz, J Hahne, B Hammer Proceedings of the 25th european symposium on artificial neural networks …, 2017 | 5 | 2017 |
Unsupervised Dimensionality Reduction for Transfer Learning P Blöbaum, A Schulz, B Hammer Proceedings. 23rd European Symposium on Artificial Neural Networks …, 2015 | 5 | 2015 |
How to visualize a classifier A Schulz, A Gisbrecht, K Bunte, B Hammer New Challenges in Neural Computation, 2012 | 5 | 2012 |
Reservoir memory machines B Paaßen, A Schulz arXiv preprint arXiv:2003.04793, 2020 | 4 | 2020 |
Efficient kernelisation of discriminative dimensionality reduction A Schulz, J Brinkrolf, B Hammer Neurocomputing 268, 34-41, 2017 | 4 | 2017 |