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Meta-Learning in Neural Networks: A Survey (Hospedales, 2020)
| tags: [ paper_summary ml ]
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Deep Mean Function Meta Learning Gaussian Processes (Fortuin, 2019)
| tags: [ paper_summary ml ]
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Model-agnostic meta-learning (MAML)
| tags: [ ml ]
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EfficientNet
| tags: [ ml ]
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Neural Architecture Search
| tags: [ ml ]
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Inductive Bias
| tags: [ ml ]
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Deep Learning
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Gaussian Processes (GP)
| tags: [ ml ]
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Nonparametric Vs Parametric Methods
| tags: [ ml comparison ]
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KL Divergence
| tags: [ ml information_theory ]
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P Values
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Inductive Vs Deductive
| tags: [ ml ]
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Tensor Networks
| tags: [ ml ]
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Clever Hans Effect
| tags: [ ml ]
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Batch Norm For Flows
| tags: [ ml ]
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Activation Normalization (Act Norm)
| tags: [ ml ]
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Learning Rate Scheduling/Warm-up
| tags: [ ml ]
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L2 Regularization
| tags: [ ml ]
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L2 With Batch Norm
| tags: [ ml ]
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Batch Normalization
| tags: [ ml ]
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Meta Learning
| tags: [ meta_learning ]
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Empirical Bayes
| tags: [ ml ]
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Implicit Maximum Likelihood Estimation (IMLE) by Ke Li
| tags: [ ml ]
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On Statistical Thinking In Deep Learning
| tags: [ ml ]
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Linear Regression
| tags: [ ml ]
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Pseudoinverse
| tags: [ ml ]
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Gaussian Processes: Discriminative or Generative?
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Generative Vs Discriminative
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Naive Bayes
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Deep Neural Networks And Gaussian Processes
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Nonparametric Methods
| tags: [ ml ]