Ecosyste.ms: Awesome

An open API service indexing awesome lists of open source software.

awesome-neural-trees

Introduction, selected papers and possible corresponding codes in our review paper "A Survey of Neural Trees"
https://github.com/zju-vipa/awesome-neural-trees

[Paper
[Paper - Guided Prototype Learning" [[Paper]](https://arxiv.org/pdf/2007.03047.pdf), two methods incorporating the class hierarchy into the regulariser of the general objective function in section 3. Although a regulariser is certainly feasible in utilize the class hierarchy, it is curiously rare in practice and these two methods are the only two examples we know of.
[Paper - box model by distilling its knowledge into decision trees, belonging to section 2.2.
[Paper
[Paper
[Paper
entropy net
[Paper
[Paper
[Paper
[Paper
[Paper
[Paper
[Paper
[Paper
[Paper
[Paper
[Paper
[Paper
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[Paper
[Paper
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[Paper
[Paper
[Paper
[Paper
[Paper
[Paper
[Paper
[Paper
[Paper
[Paper
[Paper - gates/GIRP)
[Paper
[Paper - regularization-public)
[Paper
[Paper
[Paper
Bertinetto *et al.*
[Paper
[Paper
[Paper - Zheng/HD-CNN)
[Paper - CV/Fine-Grained-or-Not)
[Paper
[Paper
[Paper
[Paper
[Paper
[Paper - HMCNN)
[Paper
[Paper
[Paper
[Paper - graph)
[Paper
[Paper
[Paper - embeddings)
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[Paper
[Paper
[Paper
[Paper
[Paper
[Paper
[Paper
[Paper
[Paper
[Paper
[Paper
[Paper - tree)
[Paper
[Paper
[Paper
[Paper
[Paper
[Paper
[Paper
[Paper - pytorch-image-models)
[Paper - decision-tree)
[Paper
[Paper - Decision-Forests)
[Paper
[Paper
[Paper - Nauta/ProtoTree)
[Paper
[Paper
[Paper
[Paper - decision-tree)
[Paper
[Paper
[Paper
[Paper
[Paper
[Paper
[Paper
[Paper
[Paper
[Paper - NeT)
[Paper
[Paper - paddle)