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It seems that core_vec does not use vectorized operation at all, the code simple_spread_n100, n_200 all use the original mpe computation.
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Requested feature:
adding a cvxpy DCP atom for the (vectorized) function f(x) = log(1-exp(-exp(x)))
Rationale:
log(1 + exp(x)) is a (non-syntactically) convex function, which is useful for th…
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Emcee allows for vectorized calls to the log-likelihood function by setting `vectorize=True` in the [EnsembleSampler](https://emcee.readthedocs.io/en/stable/user/sampler/?highlight=run_mcmc#the-ensemb…
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Hello, I note that BayesianTools package requires the likelihood function to be vectorized for parallel computation. However, it seems that the package will run anyway with option parallel = T, even i…
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This is from the PyTorch CI, but I can also reproduce with a self-built NVFuser:
Internal assert:
```
Traceback (most recent call last):
File "/usr/local/lib/python3.11/dist-packages/nvfuser/__init…
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Just a small correction to the readme file: the interpolation function I wrote already handles evaluations at multiple points, as indicated by the docstring [here](https://github.com/jstac/sdfs_via_au…
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Description:
The core algorithm in the project may not be optimized for performance, particularly when dealing with large inputs. This can result in longer execution times and higher resource usage, …
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The online free ebook is quite useful. However, unlike the structures of the online ones, the jupyter notebooks of this repository lacks enough Markdown cells ——using something as follows(just the exa…
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Current [benchmarks](https://github.com/rugheid/Swift-MathEagle/tree/master/MathEagleTests/Benchmarking%20Files) are not entirely representative of the performance, as simple vectorized computations a…
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add a standalone, reusable function with options
multivariate version is used in discrete_margins, we had brief discussion, my version is in miscmodels
one issues is how to handle different multi-di…