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4/28-29. Two-day long conference.
Quite a lot of lab members will attend this (I really hope so). See #21.
We need a couple of volunteers to make this more fun. For example:
- [ ] set up local…
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We can consider adding support for the following variational inference methods to Turing
1. Automatic derivatives variational inference [1,4]
2. Variational inference with normalizing flows [2]
3…
yebai updated
2 years ago
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Hi,
I am working with this for quite some time to replicate onto my own thesis, but I am having some troubles understanding how the Jacobian is calculated.
Can someone share some insight? Or po…
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**Submitting author:** @conorheins (Conor Heins)
**Repository:** https://github.com/infer-actively/pymdp
**Branch with paper.md** (empty if default branch): master
**Version:** v0.0.5
**Editor:** @emd…
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We have recently encountered a strange bug which manifested itself in `nan` values resulting from the computation - specifically in the gradient computation - under specific circumstances which I'll t…
lumip updated
2 years ago
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Dear Gpytorch Developers,
Thanks for the great software. I'm trying to follow the GPLVM example here:
https://docs.gpytorch.ai/en/stable/examples/045_GPLVM/Gaussian_Process_Latent_Variable_Mod…
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Hello dear community,
K_xx denotes the matrix containing all pairs of kernel entries [1].
% python -m pip install .
(venv)% python -m pip insta…
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Stochastic Variational Inference can be used to do online optimization of Bayesian/latent variable models, such as finite mixtures of Gaussians / Bernoullis - this is faster than batch EM for large da…
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Hi,
I already talked with Ólavur about this and would like to suggest adding [Structural Topic Models](http://www.structuraltopicmodel.com/) to gensim. ``STM``'s are basically (besides other thing…