Seuraa
Alexander Schulz
Alexander Schulz
Technical Faculty, CITEC, Bielefeld University
Vahvistettu sähköpostiosoite verkkotunnuksessa techfak.uni-bielefeld.de - Kotisivu
Nimike
Viittaukset
Viittaukset
Vuosi
Parametric nonlinear dimensionality reduction using kernel t-SNE
A Gisbrecht, A Schulz, B Hammer
Neurocomputing, 2015
3152015
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
622019
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
53*2017
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
402019
Expectation maximization transfer learning and its application for bionic hand prostheses
B Paaßen, A Schulz, J Hahne, B Hammer
Neurocomputing 298, 122-133, 2018
372018
Using discriminative dimensionality reduction to visualize classifiers
A Schulz, A Gisbrecht, B Hammer
Neural Processing Letters 42 (1), 27-54, 2015
362015
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
242020
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
162014
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
152021
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
142016
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
132023
Inferring feature relevances from metric learning
A Schulz, B Mokbel, M Biehl, B Hammer
Computational Intelligence, 2015 IEEE Symposium Series on, 2015
112015
How to Visualize Large Data Sets?
B Hammer, A Gisbrecht, A Schulz
Advances in Self-Organizing Maps, 2013
112013
Reservoir memory machines as neural computers
B Paaßen, A Schulz, TC Stewart, B Hammer
IEEE Transactions on Neural Networks and Learning Systems, 2021
72021
Echo state networks as novel approach for low-cost myoelectric control
C Prahm, A Schulz, B Paaßen, O Aszmann, B Hammer, G Dorffner
Conference on Artificial Intelligence in Medicine in Europe, 338-342, 2017
62017
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
52017
Unsupervised Dimensionality Reduction for Transfer Learning
P Blöbaum, A Schulz, B Hammer
Proceedings. 23rd European Symposium on Artificial Neural Networks …, 2015
52015
How to visualize a classifier
A Schulz, A Gisbrecht, K Bunte, B Hammer
New Challenges in Neural Computation, 2012
52012
Measuring fairness with biased data: a case study on the effects of unsupervised data in fairness evaluation
S Schröder, A Schulz, I Tarakanov, R Feldhans, B Hammer
International Work-Conference on Artificial Neural Networks, 134-145, 2023
42023
So Can We Use Intrinsic Bias Measures or Not?
S Schröder, A Schulz, P Kenneweg, B Hammer
ICPRAM, 403-410, 2023
42023
Järjestelmä ei voi suorittaa toimenpidettä nyt. Yritä myöhemmin uudelleen.
Artikkelit 1–20