解讀 Gaussian Boson Sampling for finding dense subgraphs
上篇博文，我們介紹了Arrazola在2018年發表的《Quantum approximate optimization with Gaussian boson sampling》文章，文中提到：如何利用Gaussian boson sampling 去加速隨機優化算法、模擬退火算法和貪婪算法去求解Max-Hafinian問題。 其實，在同時，Arrazola又發表了一篇《Using Gaussi
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相關文章
- 1. 解讀 Gaussian Boson sampling for perfect matchings of arbitrary graphs
- 2. Focal Loss for Dense Object Detection解讀
- 3. 論文解讀Focal Loss for Dense Object Detection
- 4. [論文解讀] DSD -- Dense-Sparse-Dense Training for Neural Network
- 5. 論文瀏覽(36) Finding Action Tubes with a Sparse-to-Dense Framework
- 6. Focal Loss for Dense Object Detection
- 7. 論文解讀《Almost Unsupervised Learning for Dense Crowd Counting》AAAI2019
- 8. 論文解讀《CrowdNet: A Deep Convolutional Network for Dense Crowd Counting》ACMM-MM2016
- 9. 論文閱讀筆記：Scheduled Sampling for Transformers
- 10. 【文章閱讀】【超解像】--Residual Dense Network for Image Super-Resolution