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What should I do when my neural network doesn't generalize well?

neural-networks overfitting faq asked Sep 7, 2018 at 9:12

stats.stackexchange.com

56 votes

Associate ipynb files with Jupyter notebook in Windows 10 (Anaconda)

windows anaconda jupyter-notebook jupyter asked Nov 13, 2017 at 15:32

stackoverflow.com

52 votes

What is it meant with the $\sigma$-algebra generated by a random variable?

probability random-variable sigma-algebra asked Nov 7, 2017 at 15:45

stats.stackexchange.com

41 votes

Which statistical model is being used in the Pfizer study design for vaccine efficacy?

bayesian power-analysis epidemiology clinical-trials relative-risk asked Nov 17, 2020 at 10:14

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34 votes

What are attention mechanisms exactly?

time-series deep-learning lstm rnn attention asked May 4, 2018 at 17:20

stats.stackexchange.com

31 votes

Consequences of the Gaussian correlation inequality for computing joint confidence intervals

normal-distribution confidence-interval multivariate-normal asked Mar 29, 2017 at 19:10

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27 votes

Debugging code in R Markdown

r debugging rmarkdown asked Mar 15, 2017 at 16:58

stackoverflow.com

23 votes

Simplest way to delete a "composite" word?

cursor-motions normal-mode asked Nov 5, 2018 at 10:00

vi.stackexchange.com

22 votes

Showing that 100 measurements for 5 subjects provide much less information than 5 measurements for 100 subjects

mixed-model variance repeated-measures sample-size intraclass-correlation asked Jul 30, 2017 at 18:17

stats.stackexchange.com

22 votes

pip not installing modules

python numpy pip asked Nov 30, 2015 at 10:10

stackoverflow.com

Top Answers

CNN architectures for regression?

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What are the main theorems in Machine (Deep) Learning?

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What are variational autoencoders and to what learning tasks are they used?

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Why is the mean function in Gaussian Process uninteresting?

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Prediction interval for binomial random variable

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What should I do when my neural network doesn't learn?

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Why second order SGD convergence methods are unpopular for deep learning?

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Why is increasing the non-linearity of neural networks desired?

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Should I teach Bayesian or frequentist statistics first?

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Do Gaussian process (regression) have the universal approximation property?

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What should I do when my neural network doesn't generalize well?

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Beta distribution on flipping a coin

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What're the differences between PCA and autoencoder?

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What is the essential difference between a neural network and nonlinear regression?

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How large exactly is the mosasaurus in Jurassic World?

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How should I standardize input when fine-tuning a CNN?

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What is a distribution over functions?

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Why Hamiltonian dynamics is better than random walk proposal in MCMC in some cases?

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Gaussian process prediction interval

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interpretation of the output of R function bs() (B-spline basis matrix)

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Multi-layer perceptron vs deep neural network

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Bayesian updating - coin tossing example

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Do Autoencoders preserve distances?

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Can it be over fitting when validation loss and validation accuracy is both increasing?

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Criteria for choosing a mean function for a GP

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Convolutional Neural Network Scale Sensitivity

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how to find the coefficient for the construction of the linear regression model (using Fourier )?

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Confused in selecting the number of hidden layers and neurons in an MLP for a binary classification problem

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What are the best books to study Neural Networks from a purely mathematical perspective?

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From a statistical perspective: Fourier transform vs regression with Fourier basis

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