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### Please describe the purpose of the new feature or describe the problem to solve.
I would be great to have support for ND convolution of sparse arrays. Basically an implementation of `scipy.signal…
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Use sparse convolution with the PSF in the simulation to avoid conversion to a dense matrix. This can save memory and be much faster.
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While studying autoencoder architecture, I discovered that the similar terms "transposed convolution" and "deconvolution" have caused some confusion. I would like to clarify their differences and expl…
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## DoD
- [ ] Introduction of what this notebook does: Certified Coordinates Selection (CCS) for dimension reduction with Laplace prior and wavelets for sparse representation of signal
- [ ] Descript…
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### Motivation and description
For many applications (graph neural networks, 3d point clouds, ...) sparse convolution would be a cool feature
### Possible Implementation
A guide to implementation i…
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hi,when pytorch can support sparse convolution in pytroch master?thanks.
cc @vincentqb
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https://github.com/huang-yh/GaussianFormer/blob/3bf28d50b41c8a54fda8147defe52a08f1a05b4e/model/encoder/gaussian_encoder/spconv3d_module.py#L53-L67
Although interaction can be efficient using spar…
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logつくけど殴れる！みたいなのは除くものとする
library checkerのカテゴリ変更に対応していません
https://judge.yosupo.jp/
# New
- [ ] Matrix Product (Mod 2) (#364)
- [ ] Multiplication of Hex Big Integers
- [ ] Intersection of F_2 vec…
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Hi,
I was wondering if you were planning to implement a 3D version of Instanseg. By this, I mean true 3D segmentation with 3D convolution operations.
At the moment I'm using Cellstitch with Cellpo…
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if we get a sparse model, is there an effective way to do sparse convolutional for inference? I just know 2015 CVPR paper "Sparse Convolutional Neural Networks", is there exit another more effective…