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I have a model that takes a scalar parameter `theta`:
```
var squish = function(x) {
return 1 / (1 + Math.exp(-x))
};
var model = function(theta) {
var p = squish(gaussian(theta, 1));
observe(…
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[Neural Adaptive SMC, Gu etc.](https://arxiv.org/abs/1506.03338) is a nice framework that allows us to train proposals for non-linear state space models. We can use [forward KL in a nested variational…
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General meta-programs for VI:
- Define a subset of variables that are assumed to always be there.
- Target those with the VI
- "Gen provides meta-programs for black box variational inference"
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link: https://arxiv.org/abs/1602.06725
So called VIMCO.
Referenced from:
- Learning Hard Alignments in Variational Inference #329
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As someone involved in the recent tsdate releases, I'm wondering how tsinfer+tsdate_v0.2.1 performs (e.g. compared to Relate). The recommended way to perform ARG inference now is
```python
import …
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Hi, everyone. I'm not sure if I am at the right place to ask, but I'll try it anyways :-)
I've been trying to implement the algorithm proposed in Tran et al. (2017) - "Hierarchical Implicit Models …
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VKM: "variational inference on a toy Bayesian linear regression example, with a naive mean field [variational] approximation, using reverse-mode AD [on a subset of Metaprob]" (see https://github.com/p…
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I know you are busy with front end refactoring, but I was excited about the possibility to do inference on larger datasets in Lora and wanted to leave this on the queue. Also may be worth keeping in …
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**Notebook title**: Introduction to Variational Inference with PyMC
**Notebook url**: https://www.pymc.io/projects/examples/en/latest/variational_inference/variational_api_quickstart.html
## Issue…
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## Rough ideas, need vetting.
- reference CTMC
- [Solving the Forecast Combination Puzzle](https://arxiv.org/pdf/2308.05263.pdf) via log-linear Hyvaarinen stacking (locking).
- Quality of sp…