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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…
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Sometimes the sparse structure of a problem can change during non-linear optimization. It would be useful to be able to update the symbolic analysis of the matrix in-place, to avoid re-allocating all …
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Right now the components are held in hash maps for O(1) access time. Most Entity Components Systems that I've read about use sparse arrays instead. The problem with a sparse array is that if you hav…
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### Please describe your wishes and possible alternatives to achieve the desired result.
## The problem
Indexing statements for backed anndata objects often look like:
```python
subset = back…
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**System information**
- TensorFlow version (you are using): 2.3
- Are you willing to contribute it (Yes/No): I can write tutorials.
**Motivation**
Sparsity is a well-studied topic in neur…
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Hi,
When I try to test it, I got error of missing BeBOP library:
checking for library containing load_sparse_matrix... no
I found BeBOP is Berkeley Benchmarking and OPtimization, and got libbeb…
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Suggested list of courses would be:
- An introduction to deep learning **
- How to train a neural network
- Regularisation in neural networks
- Deep Bayesian neural networks
- Conv…
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Hello,
Thanks for the BR method. The proposed screening method works fine.
However, for the KDD method. did you upload the wrong folder by accident? For the KDD folder, the code seems to solve t…
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```
Currently the optimization package expects the parameters to be Arrays, that
are dense in their implementation. Allowing Vector from the la package will
allow us to use sparse (or other) paramet…
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# Reading past an array bounds is unsound
While you are correct that at the machine code level, one can read past an array bounds without invoking UB -- because at the machine code level, there is …