# alecwangcq/EigenDamage-Pytorch

<https://repo.masters-masters.com/en/repos/alecwangcq/EigenDamage-Pytorch>

[Home](https://repo.masters-masters.com/en) › [alecwangcq](https://repo.masters-masters.com/en/owners/alecwangcq) › [EigenDamage-Pytorch](https://repo.masters-masters.com/en/repos/alecwangcq/EigenDamage-Pytorch)

alecwangcq/EigenDamage-Pytorch has 113 stars on GitHub. Its RepoMasters card: Prototype tier. Code for "EigenDamage: Structured Pruning in the…

| Field | Value |
| --- | --- |
| Owner | [alecwangcq](https://repo.masters-masters.com/en/owners/alecwangcq) |
| Stars | 113 |
| Forks | 18 |
| Language | [Python](https://repo.masters-masters.com/en/languages/python) |
| License | MIT |
| Created | 2019 |
| Topics | network-pruning, deep-learning, machine-learning, fisher-matrix, pytorch |
| Tier | [Prototype (100 to 249 ★)](https://repo.masters-masters.com/en/ranks/rush) |
| View on GitHub | [alecwangcq/EigenDamage-Pytorch](https://github.com/alecwangcq/EigenDamage-Pytorch) |

## Repository

Code for "EigenDamage: Structured Pruning in the Kronecker-Factored Eigenbasis" https://arxiv.org/abs/1905.05934

The tier for repos with 100 to 249 ★. Published odds per card pulled: 70%. Rarity: Common.

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Data: GitHub · Illustration drawn by RepoMasters from the repo’s ID and its language color.