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This outlines a roadmap for basic statistical functionality that Julia needs to offer. It is heavily drawn from the table of contents for MASS.
- [ ] Data processing [DataFrames.jl](https://github.com…
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Sometimes we have a discrete random variable that has type `tf.Tensor` and not `ed.RandomVariable`. The tensor has discrete values and is random due to inputs in its graph being random. For example, B…
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The paper [Weight Uncertainty in Neural Networks](https://arxiv.org/abs/1505.05424) proposes the usage of a mixture of two Gaussians as the prior distribution. By default, the priors (of the kernel an…
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Regarding the paper titled “Back to the basics: Bayesian extensions of IRT outperform neural networks for proficiency estimation”, I am interested in the online prediction accuracy metric of evaluatio…
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- [ ] Documentation
- [ ] Sample (selected) deterministic variables
- [ ] HMC from blackjax-devs/blackjax
- [ ] NUTS from blackjax-devs/blackjax
- [ ] Effective sample size from blackjax-devs/blac…
rlouf updated
3 years ago
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I've already come across different problems related to the eager execution of the TensorFlow code that involves this package. For example, https://github.com/tensorflow/probability/issues/620 (an issu…
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Can this library only use Gaussian distribution as prior distribution? Are there other prior distributions?
Another question is that if the input data and the prior distribution are Gaussian distrib…
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I think it helps to have simple toy examples where we can visualize the weights learned by the inference algorithms (for example in 2D). This is slightly different from the spiral example in scripts/a…
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I have a deep neural network model in a file called param_optimizer.py and I import the dimensions and the neural network's name to the file where I run gp_minimize():
````py
from skopt import gp_…
ISipi updated
3 years ago
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