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Hanna Wutte

Hanna S. Wutte

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Conference and Workshop Papers

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2022
[c1]
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  - conf/icml/HeissWWST22
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Jakob Heiss, Jakob Weissteiner, Hanna S. Wutte, Sven Seuken, Josef Teichmann:
NOMU: Neural Optimization-based Model Uncertainty. ICML 2022: 8708-8758

Informal and Other Publications

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2024
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  - journals/corr/abs-2403-15243
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Florian Krach, Josef Teichmann, Hanna Wutte:
Robust Utility Optimization via a GAN Approach. CoRR abs/2403.15243 (2024)
2023
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  - journals/corr/abs-2303-11454
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Jakob Heiss, Josef Teichmann, Hanna Wutte:
How (Implicit) Regularization of ReLU Neural Networks Characterizes the Learned Function - Part II: the Multi-D Case of Two Layers with Random First Layer. CoRR abs/2303.11454 (2023)
2021
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  - journals/corr/abs-2102-13640
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Jakob Heiss, Jakob Weissteiner, Hanna Wutte, Sven Seuken, Josef Teichmann:
NOMU: Neural Optimization-based Model Uncertainty. CoRR abs/2102.13640 (2021)
[i2]
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  dblp key:
  - journals/corr/abs-2112-15577
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Jakob Heiss, Josef Teichmann, Hanna Wutte:
Infinite wide (finite depth) Neural Networks benefit from multi-task learning unlike shallow Gaussian Processes - an exact quantitative macroscopic characterization. CoRR abs/2112.15577 (2021)
2019
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  - journals/corr/abs-1911-02903
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Jakob Heiss, Josef Teichmann, Hanna Wutte:
How implicit regularization of Neural Networks affects the learned function - Part I. CoRR abs/1911.02903 (2019)

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