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Hi,
Are there any implementations where the scaled conjugate gradient (: SCG) method is used to optimize the model's hyperparameters, instead of LBFGS or the stochastic gradient descent?
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### Description
Providing a way to enable `float64` without changing the default dtype/precision. Or even better, adding the option to choose the default dtype. For example,
```python
jax.confi…
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Pearlmutter method only gives "good" value of hessian vector product in the first two iterations in conjugate gradient loop
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Both `conjugate_gradient_normal` and `landweber` assumes the range of the operator is a `LinearSpace`. For `Functional`s this will typically be `RealNumbers` and they both give errors:
```
>>> odl.so…
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Seems that https://github.com/CliMA/Oceananigans.jl/pull/2412/ suggests that this is the fastest way for grids that don't have regular horizontal spacing or have an immersed boundary.
Yet, the fre…
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I'm not sure whether this is the right place to ask my question but here we go:
I'm currently trying to speed up gaussian processes by using the Wendland kernel (https://github.com/cornellius-gp/gpyt…
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As we discovered when looking at the L-BFGS optimiser (#1083 ) line search algorithms are not that straightforward and are an integral part of Quasi-Newton and conjugate gradient methods. Furthermore,…
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Hello!
First of all, thank you for your great work, I am using your library a lot and it's very efficient in removing background!
My issue is that recently I started getting this error after pro…
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Just as a tangent-linear computes a general directional derivative (a JAX `jvp`) the adjoint computes a (conjugate) derivative of a general dual element evaluation (the conjugate of a JAX `vjp`).
F…
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Add an argument which will toggle whether or not the conjugate gradient solve step in `hydra_pspec.pspec.gcr_fgmodes_1d` uses the previous solution as the initial guess (`x0`).