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- id: DomingosEvery2020
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      day: 12
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      day: 10
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      day: 21
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- id: FortDeep2020
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  language: en
  title: >-
    Deep learning versus kernel learning: an empirical study of loss landscape
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- id: GalTheoretically2016
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- id: GeifmanSimilarity2020
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      month: 11
      day: 14
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- id: GhahramaniBayesian2013
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- id: GiryesDeep2016
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- id: HeBayesian2020
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  issued:
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  title: Bayesian Deep Ensembles via the Neural Tangent Kernel
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- id: JacotNeural2018
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  language: en
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      month: 12
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  container-title: Advances in Neural Information Processing Systems
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  language: en
  title: >-
    Understanding Approximate Fisher Information for Fast Convergence of Natural
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- id: KristiadiInfinitefeature2021
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  title: >-
    An infinite-feature extension for Bayesian ReLU nets that fixes their
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  title: Inter-domain Gaussian Processes for Sparse Inference using Inducing Features
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    - family: Pennington
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  citation-key: LeeDeep2018
  container-title: ICLR
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      month: 3
      day: 2
  language: en
  title: Deep Neural Networks as Gaussian Processes
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    - family: Novak
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      day: 8
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  title: Stationary Activations for Uncertainty Calibration in Deep Learning
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  citation-key: NealPriors1996
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  language: en
  page: 29-53
  publisher: Springer
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      month: 8
      day: 21
  title: >-
    Bayesian Deep Convolutional Networks with Many Channels are Gaussian
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- id: NovakNeural2019
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      month: 1
      day: 4
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  issued:
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      month: 12
      day: 5
  title: 'Neural Tangents: Fast and Easy Infinite Neural Networks in Python'
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- id: PearceExpressive2019
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  citation-key: PearceExpressive2019
  container-title: Uncertainty in Artificial Intelligence
  issued:
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  language: en
  page: '11'
  title: >-
    Expressive Priors in Bayesian Neural Networks: Kernel Combinations and
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- id: RossiSparse2021
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      day: 31
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    - family: Heinonen
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    - family: Bonilla
      given: Edwin
    - family: Shen
      given: Zheyang
    - family: Filippone
      given: Maurizio
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  event-title: International Conference on Artificial Intelligence and Statistics
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      day: 18
  language: en
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  publisher: PMLR
  title: >-
    Sparse Gaussian Processes Revisited: Bayesian Approaches to
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    - family: Dhaliwal
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      day: 12
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- id: ShiSparse2020
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  collection-title: NIPS'96
  container-title: >-
    Proceedings of the 9th International Conference on Neural Information
    Processing Systems
  event-place: Cambridge, MA, USA
  event-title: NIPS
  issued:
    - year: 1996
      month: 12
      day: 3
  language: en
  page: 295–301
  publisher: MIT Press
  publisher-place: Cambridge, MA, USA
  title: Computing with infinite networks
  type: paper-conference
  URL: https://openreview.net/forum?id=S1V2dDbdZH

- id: YangFeature2020
  accessed:
    - year: 2021
      month: 1
      day: 4
  author:
    - family: Yang
      given: Greg
    - family: Hu
      given: Edward J.
  citation-key: YangFeature2020
  container-title: arXiv:2011.14522 [cond-mat]
  issued:
    - year: 2020
      month: 11
      day: 29
  title: Feature Learning in Infinite-Width Neural Networks
  type: article-journal
  URL: http://arxiv.org/abs/2011.14522

- id: YangTensor2019
  accessed:
    - year: 2021
      month: 1
      day: 4
  author:
    - family: Yang
      given: Greg
  citation-key: YangTensor2019
  container-title: arXiv:1910.12478 [cond-mat, physics:math-ph]
  issued:
    - year: 2019
      month: 12
      day: 7
  title: >-
    Tensor Programs I: Wide Feedforward or Recurrent Neural Networks of Any
    Architecture are Gaussian Processes
  type: article-journal
  URL: http://arxiv.org/abs/1910.12478

- id: ZhangUnderstanding2017
  author:
    - family: Zhang
      given: Chiyuan
    - family: Bengio
      given: Samy
    - family: Hardt
      given: Moritz
    - family: Recht
      given: Benjamin
    - family: Vinyals
      given: Oriol
  citation-key: ZhangUnderstanding2017
  container-title: Proceedings of ICLR
  event-title: ICLR
  issued:
    - year: 2017
  title: Understanding deep learning requires rethinking generalization
  type: paper-conference
  URL: http://arxiv.org/abs/1611.03530
...
