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- [ ] Add support for [SINGD](https://github.com/f-dangel/singd) baseline. This enables structured Kronecker factors, e.g. diag & full, sparse, etc.
- [ ] Update `KronLaplace` and `matrix.py` to acco…
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### Problem
When performing consecutive linear algebra computations on `probnum.linops.LinearOperator`s, in which the result is a `LinearOperator`, which is then further processed in `LinearOperat…
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### Description
[This paper ](https://arxiv.org/abs/2309.03060) and [this library ](https://github.com/wilson-labs/cola)describe and implement a number of linear algebra simplifications that we can…
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Hi there, great work so far!
I don't think it is possible to fit variance-covariance matrices that are the Kronecker product (_a.k.a._ direct product) of mutiple terms in the model. I am only assumin…
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So recently we had a user who wanted to model multiple assessments per visit per subject. We currently cannot model this adequately with the existing covariance structure framework, because:
1) we …
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Sampling from a matrix-normal distribution with two symmetric matrices making up a Kronecker structured covariance doesn't produce symmetric samples.
This could possibly be enforced by checking sym…
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I've placed a barebones parser in `dev/eqn_parser.R` which implements some of the ideas I was thinking w.r.t. reducing the amount of LaTeX code for the novice user, but still allow power users freedom…
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We currently delazify the Cholesky decomposition inside `MultivariateNormal`: https://github.com/cornellius-gp/gpytorch/blob/8f9b44fc57dbb0a13b568946f07a37e9332f92c4/gpytorch/distributions/multivariat…
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Consider a kernel of the form
```julia
(k)(x::Vector, x′::Vector) = prod(map(k.ks, x, x′))
```
where `k.ks` is a collection of kernels which can be applied to single-dimensions, and the dimensiona…
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How to we handle t_test and wald_test generically for models that have "naturally" 2-dimensional params?
examples: currently VAR, Multinomial, more are coming VECM, SUR, ...
one option would be to r…