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Veit Wild

Veit D. Wild – Veit David Wild

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2023
[c3]
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  dblp key:
  - conf/nips/WildGSK23
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Veit David Wild, Sahra Ghalebikesabi, Dino Sejdinovic, Jeremias Knoblauch:
A Rigorous Link between Deep Ensembles and (Variational) Bayesian Methods. NeurIPS 2023
[i4]
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  - journals/corr/abs-2305-15027
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Veit David Wild, Sahra Ghalebikesabi, Dino Sejdinovic, Jeremias Knoblauch:
A Rigorous Link between Deep Ensembles and (Variational) Bayesian Methods. CoRR abs/2305.15027 (2023)
2022
[j1]
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  - journals/jcgs/ZhangWFFS22
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Qinyi Zhang, Veit Wild, Sarah Filippi, Seth R. Flaxman, Dino Sejdinovic:
Bayesian Kernel Two-Sample Testing. J. Comput. Graph. Stat. 31(4): 1164-1176 (2022)
[c2]
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  - conf/aistats/WynneW22
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George Wynne, Veit Wild:
Variational Gaussian Processes: A Functional Analysis View. AISTATS 2022: 4955-4971
[c1]
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Veit D. Wild, Robert Hu, Dino Sejdinovic:
Generalized Variational Inference in Function Spaces: Gaussian Measures meet Bayesian Deep Learning. NeurIPS 2022
[i3]
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  - journals/corr/abs-2205-06342
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Veit D. Wild, Robert Hu, Dino Sejdinovic:
Generalized Variational Inference in Function Spaces: Gaussian Measures meet Bayesian Deep Learning. CoRR abs/2205.06342 (2022)
2021
[i2]
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  - journals/corr/abs-2106-01121
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Veit Wild, Motonobu Kanagawa, Dino Sejdinovic:
Connections and Equivalences between the Nyström Method and Sparse Variational Gaussian Processes. CoRR abs/2106.01121 (2021)
[i1]
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  - journals/corr/abs-2110-12798
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Veit Wild, George Wynne:
Variational Gaussian Processes: A Functional Analysis View. CoRR abs/2110.12798 (2021)

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