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Hi,
I tried to implement the `bayesian_rnn` from the docs.
However, while trying to compute `log_joint`, I can't compute the log of prior `log_pz` because `w` is declared within a LSTM cell, so I …
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the original setting of latent space p(X) is i.i.d Gaussian distribution.
However, I want to place a Gaussian Processes prior on the latent space p(X)~GP(0,k_{t,t'})
Is GPflow able to do this?
If c…
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I am considering using pyro for my problem, but I don't quite grok the library yet. Part of my confusion comes from SVI being the main well documented inference engine in pyro, and I am a beginner to…
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I was trying to figure out where exactly the noise is being added inside the kernel elements of each layer.
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Hi,
I'm using GPy.core.SVGP for large datasets; I'm trying to understand the implementation better. Here is code from your tutorials;
```
N=5000
X = np.random.rand(N)[:, None]
Y1 = np.sin(6*X) + 0.…
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I implemented normalizing flows in ADVI and tested it on a beta-binomial model ([notebook](https://gist.github.com/taku-y/43550e688f4020ac7da15a181d262f2f#file-pymc3_normalizing_flow_beta_binomial-ipy…
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Curious why all the params are auto-magically global with a shared namespace. Seems like a very different design choice than the nice cleanly scoped pytorch variables.
srush updated
6 years ago
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Hi,
I am using MatlabStan to infer parameters of the following model:
data {
int N; //number of time intervals
int J; //number of sections
real y[N,J]; //data points for corrosi…
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Implement the technique in this paper by Abbeel's group: https://arxiv.org/pdf/1506.05254.pdf
This should allow us to very concisely express variational autoencoders.
It's a very cool technique, and…
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Hamiltonian Monte Carlo (HMC), also known as Hybrid Monte Carlo, is an efficient Markov Chain Monte Carlo (MCMC) method that exploits gradient information to improve on the simpler MCMC methods. See t…