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Marissa A. Weis
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Books and Theses
- 2024
- [b1]Marissa A. Weis:
Unsupervised Representation Learning for Object-Centric and Neuronal Morphology Modeling. Tübingen University, Germany, 2024
Journal Articles
- 2023
- [j2]Marissa A. Weis, Laura Pede, Timo Lüddecke, Alexander S. Ecker:
Self-Supervised Graph Representation Learning for Neuronal Morphologies. Trans. Mach. Learn. Res. 2023 (2023) - 2021
- [j1]Marissa A. Weis, Kashyap Chitta, Yash Sharma, Wieland Brendel, Matthias Bethge, Andreas Geiger, Alexander S. Ecker:
Benchmarking Unsupervised Object Representations for Video Sequences. J. Mach. Learn. Res. 22: 183:1-183:61 (2021)
Conference and Workshop Papers
- 2019
- [c2]Elliot Creager, David Madras, Jörn-Henrik Jacobsen, Marissa A. Weis, Kevin Swersky, Toniann Pitassi, Richard S. Zemel:
Flexibly Fair Representation Learning by Disentanglement. ICML 2019: 1436-1445 - 2018
- [c1]Santiago A. Cadena
, Marissa A. Weis, Leon A. Gatys, Matthias Bethge, Alexander S. Ecker
Diverse Feature Visualizations Reveal Invariances in Early Layers of Deep Neural Networks. ECCV (12) 2018: 225-240
Informal and Other Publications
- 2024
- [i5]Polina Turishcheva, Laura Hansel, Martin Ritzert, Marissa A. Weis, Alexander S. Ecker:
MNIST-Nd: a set of naturalistic datasets to benchmark clustering across dimensions. CoRR abs/2410.16124 (2024) - 2021
- [i4]Marissa A. Weis, Laura Pede, Timo Lüddecke, Alexander S. Ecker:
Self-supervised Representation Learning of Neuronal Morphologies. CoRR abs/2112.12482 (2021) - 2020
- [i3]Marissa A. Weis, Kashyap Chitta, Yash Sharma, Wieland Brendel, Matthias Bethge, Andreas Geiger, Alexander S. Ecker
Unmasking the Inductive Biases of Unsupervised Object Representations for Video Sequences. CoRR abs/2006.07034 (2020) - 2019
- [i2]Elliot Creager, David Madras, Jörn-Henrik Jacobsen, Marissa A. Weis, Kevin Swersky, Toniann Pitassi, Richard S. Zemel:
Flexibly Fair Representation Learning by Disentanglement. CoRR abs/1906.02589 (2019) - 2018
- [i1]Santiago A. Cadena, Marissa A. Weis, Leon A. Gatys, Matthias Bethge, Alexander S. Ecker:
Diverse feature visualizations reveal invariances in early layers of deep neural networks. CoRR abs/1807.10589 (2018)
Coauthor Index
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