-
Hello, it seems that new version doesn't support approximate bayesian computation any more. However, in main `DiffEqBayes.jl`, `abc_inference` is exported. Also, codes of example of README implies tha…
-
Hello,
I tried the 'Optimization Tutorial' (https://amoeba2.readthedocs.io/en/latest/notebooks/optimization.html) and when I copy and paste the code exactly to optimise the fit of the simulated dat…
-
Most of methods in the list will be implemented in the order.
- inference for Sparse Gaussian process regression (based on JMLR 2005 "A unifying view of sparse approximate Gaussian process regression…
-
I'm trying to implement the GP with a Poisson likelihood whose parameter may vary with the observations[^1]:
$$ y_i \sim Poisson(e_i exp(f_i))$$
where f_i is the GP. Is this possible?
[^1]: [App…
-
has anyone successfully deployed on orin? what's the infer time like?
-
Are there ways to reduce the amount of VRAM consumption? For example like how the Open-Sora-Plan team reduced the number of CausalConv3D layers in the encoder? As from the paper, it seems like batch …
-
We can compare to this JMLR paper : [Stochastic Gradient Descent as Approximate Bayesian Inference](https://arxiv.org/abs/1704.04289).
They have experiments which are easier to work with : Linear Reg…
-
https://github.com/google/bayesnf/blob/fb59400ab86aa16a548f6df566bc0d5ba6e19eb5/src/bayesnf/inference.py#L445
If `ensemble_size < jax.device_count` then 0 particles are fitted.
In terms of the A…
fsaad updated
7 months ago
-
The use of a GAN in the null space for superresolution have already been done, first in C. Sonderby, J. Caballero, L. Theis, W. Shi, and F. Huszar, “Amortised MAP inference for image super-resolution,…
-
This is intended as a discussion issue where we can hash out an initial design for the package. The goal is to
1. tie down the structure of the package, including how the internals should be design…