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### Algorithm
- [ ] (simulation) Is there any advantage of similarity transformation over unitary transformation in terms of reducing negative elements in matrix?
- [x] (simulation) develop algo…
MKrbm updated
7 months ago
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Post a link for a "possibility" reading of your own on the topic of Network & Table Learning [for week 6], accompanied by a 300-400 word reflection that: 1) briefly summarizes the article (e.g., as we…
lkcao updated
2 years ago
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This example generates an incorrect descent direction in L-BFGS:
```julia
using Manopt, Manifolds, LineSearches
function f_rosenbrock_manopt(::AbstractManifold, x)
result = 0.0
for i in…
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hi,
Your package is written very well. Thank you very much for your reply. By reading your doctoral dissertation, I can understand your package.However, I encountered some minor issues.
The foll…
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Hi, I'm trying to implement a custom metric on $\mathbb{R}^n$. My goal is to test out the built-in ODE geodesic solver when I fully specify the metric as a matrix function (e.g., g= local_metric(M, p…
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## 🐛 Bug
I am getting different derivatives when I compute `g(A)` via `A -> g(A)` versus `A -> LL' -> g(LL')`. The derivatives are off in a predictable way, and it's easy to correct (~2 lines of code…
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I'm trying to understand the implementation of Riemannian Adam in `radam.py` and am comparing it to the psuedo-code in the reference paper [Riemanian Adaptive Optimization Methods](https://arxiv.org/p…
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This thread -- as a continuation of the discussion started in JuliaManifolds/Manifolds.jl#27 -- shall collect ideas and approaches to the Riemannian Gradient (for example employing tools like the `eg…
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Is this just the identity?
I'm by no means a geometer and am probably way off base, but from what I can gather reading some articles about parallel transport, I think since the simplex is flat ever…