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Bernhard Schäfl
Bernhard Schäfl
Research Scientist, University of Natural Resources and Life Sciences, Vienna (BOKU)
Bestätigte E-Mail-Adresse bei ml.jku.at
Titel
Zitiert von
Zitiert von
Jahr
Hopfield networks is all you need
H Ramsauer, B Schäfl, J Lehner, P Seidl, M Widrich, T Adler, L Gruber, ...
International Conference on Learning Representations, 2021
4272021
Modern hopfield networks and attention for immune repertoire classification
M Widrich, B Schäfl, M Pavlović, H Ramsauer, L Gruber, M Holzleitner, ...
Advances in Neural Information Processing Systems 33, 18832-18845, 2020
1132020
Modern Hopfield Networks as Memory for Iterative Learning on Tabular Data
B Schäfl, L Gruber, A Bitto-Nemling, S Hochreiter
Associative Memory & Hopfield Networks in 2023, 2023
20*2023
DeepRC: immune repertoire classification with attention-based deep massive multiple instance learning
M Widrich, B Schäfl, M Pavlović, GK Sandve, S Hochreiter, V Greiff, ...
BioRxiv 2020, 038158, 2020
142020
A GAN based solver of black-box inverse problems
M Gillhofer, H Ramsauer, J Brandstetter, B Schäfl, S Hochreiter
NeurIPS 2019 Workshop on Solving Inverse Problems with Deep Networks, 2019
32019
G-Signatures: Global Graph Propagation With Randomized Signatures
B Schäfl, L Gruber, J Brandstetter, S Hochreiter
arXiv preprint arXiv:2302.08811, 2023
12023
Utilizing Explicit and Implicit Memory in Deep Neural Networks/submitted by Bernhard Franz Schäfl
BF Schäfl
2023
An LSTM-based approach for coiled-coil domain prediction
B Schäfl
Universität Linz, 2018
2018
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