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Michael Widrich
Michael Widrich
Research Assistant at Institute for Machine Learning, Johannes Kepler University Linz
Verified email at ml.jku.at - Homepage
Title
Cited by
Cited by
Year
Speeding up semantic segmentation for autonomous driving
M Treml, J Arjona-Medina, T Unterthiner, R Durgesh, F Friedmann, ...
2432016
Hopfield networks is all you need
H Ramsauer, B Schäfl, J Lehner, P Seidl, M Widrich, T Adler, L Gruber, ...
arXiv preprint arXiv:2008.02217, 2020
1352020
Rudder: Return decomposition for delayed rewards
JA Arjona-Medina, M Gillhofer, M Widrich, T Unterthiner, J Brandstetter, ...
Advances in Neural Information Processing Systems 32, 2018
1322018
Explaining and interpreting LSTMs
L Arras, J Arjona-Medina, M Widrich, G Montavon, M Gillhofer, KR Müller, ...
Explainable ai: Interpreting, explaining and visualizing deep learning, 211-238, 2019
582019
Modern Hopfield Networks and Attention for Immune Repertoire Classification
GK Michael Widrich, Bernhard Schäfl, Hubert Ramsauer, Milena Pavlović, Lukas ...
Advances in Neural Information Processing Systems 33, 18832-18845, 2020
432020
Large-scale ligand-based virtual screening for SARS-CoV-2 inhibitors using deep neural networks
M Hofmarcher, A Mayr, E Rumetshofer, P Ruch, P Renz, J Schimunek, ...
arXiv preprint arXiv:2004.00979, 2020
422020
The immuneML ecosystem for machine learning analysis of adaptive immune receptor repertoires
M Pavlović, L Scheffer, K Motwani, C Kanduri, R Kompova, N Vazov, ...
Nature Machine Intelligence 3 (11), 936-944, 2021
222021
In silico proof of principle of machine learning-based antibody design at unconstrained scale
R Akbar, PA Robert, CR Weber, M Widrich, R Frank, M Pavlović, ...
Mabs 14 (1), 2031482, 2022
172022
Cross-domain few-shot learning by representation fusion
T Adler, J Brandstetter, M Widrich, A Mayr, D Kreil, M Kopp, G Klambauer, ...
arXiv preprint arXiv:2010.06498, 2020
152020
One billion synthetic 3D-antibody-antigen complexes enable unconstrained machine-learning formalized investigation of antibody specificity prediction
PA Robert, R Akbar, R Frank, M Pavlović, M Widrich, I Snapkov, ...
BioRXiV, 2021
112021
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, 2020.04. 12.038158, 2020
52020
Modern Hopfield Networks for Return Decomposition for Delayed Rewards
M Widrich, M Hofmarcher, VP Patil, A Bitto-Nemling, S Hochreiter
Deep RL Workshop NeurIPS 2021, 2021
42021
Cross-Domain Few-Shot Learning by Representation Fusion
T Adler, J Brandstetter, M Widrich, A Mayr, D Kreil, M Kopp, G Klambauer, ...
22021
Deep Learning Methods for Credit Assignment in Reinforcement Learning and Immune Repertoire Classification/submitted by Michael Widrich
M Widrich
2022
Long Short-Term Memory and convolutional neural networks for SNV-based phenotype prediction/submitted by Michael Widrich
M Widrich
Universität Linz, 2016
2016
Modern Hopfield Networks for Sample-Efficient Return Decomposition from Demonstrations
M Widrich, M Hofmarcher, V Patil, A Bitto-Nemling, S Hochreiter
Michael Gillhofer2, Klaus-Robert Müller3, 4, 5, Sepp Hochreiter2, and Wojciech Samek1
L Arras, J Arjona-Medina, M Widrich, G Montavon
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