欢迎提交未收录的代码

[yshenaw]

如果你知道一些相关的开源论文，但不在此列表中，非常欢迎添加在此issue当中，感谢为开源社区贡献一份力量

[revenol]

L. Huang, S. Bi, and Y. J. Zhang, “Deep reinforcement learning for online computation offloading in wireless powered mobile-edge computing networks,” IEEE Trans. Mobile Compt., vol. 19, no. 11, pp. 2581-2593, November 2020.

https://github.com/revenol/DROO

[linkpark]

J. Wang, J.Hu, G. Min, A. Y. Zomaya, and N. Georgalas, “Fast Adaptive Computation Offloading in Edge Computing based on Meta Reinforcement Learning“. IEEE Transactions on Parallel and Distributed Systems, vol. 32, no. 1, pp. 242--253, 2021.

https://arxiv.org/abs/2008.02033

https://github.com/linkpark/metarl-offloading

[Azhe9510]

建议在表格的每一行前添加序号 方便大家知道最近添加的是哪些论文代码

[zhuwenxing]

建议在表格的每一行前添加序号 方便大家知道最近添加的是哪些论文代码

一般最前面的就是新添加的，但是不能保证新添加论文发表的时间也是最新的。

[STARainZ]

K. Pratik, B. D. Rao, and M. Welling, “RE-MIMO: Recurrent and Permutation Equivariant Neural MIMO Detection,” IEEE Trans. Signal Process., vol. 69, pp. 459–473, 2021.

https://arxiv.org/abs/2007.00140

https://github.com/krpratik/RE-MIMO

[tesiawang]

F. B. Mismar, A. Alammouri, A. Alkhateeb, J. G. Andrews, and B. L. Evans, “Deep Learning Predictive Band Switching in Wireless Networks,” IEEE Transactions on Wireless Communications, vol. 20, no. 1, pp. 96–109, Jan. 2021, doi: 10.1109/TWC.2020.3023397.

https://ieeexplore.ieee.org/abstract/document/9199558

https://github.com/farismismar/Bandswitch-DeepMIMO

[tanxiangtj]

H. Chang, H. Song, Y. Yi, J. Zhang, H. He and L. Liu, "Distributive Dynamic Spectrum Access Through Deep Reinforcement Learning: A Reservoir Computing-Based Approach," in IEEE Internet of Things Journal, vol. 6, no. 2, pp. 1938-1948, April 2019, doi: 10.1109/JIOT.2018.2872441.

https://ieeexplore.ieee.org/document/8474348
https://github.com/haohsuan2918/DQN_RC_DSA_IOT2019

[tanxiangtj]

https://mlc.committees.comsoc.org/papers-with-code/

[revenol]

Suzhi Bi, Liang Huang, Hui Wang, and Ying-Jun Angela Zhang, "Lyapunov-guided Deep Reinforcement Learning for Stable Online Computation Offloading in Mobile-Edge Computing Networks," IEEE Transactions on Wireless Communications, 2021, doi:10.1109/TWC.2021.3085319.

https://ieeexplore.ieee.org/document/9449944
https://github.com/revenol/LyDROO

[STARainZ]

H. He, C. Wen, S. Jin, and G. Y. Li, “Model-driven deep learning for MIMO detection,” IEEE Trans. Signal Process., vol. 68, pp. 1702–1715, Feb. 2020.

https://ieeexplore.ieee.org/document/9018199/
https://github.com/hehengtao/OAMP-Net

[silentsaber]

J. Choi, Y. Cho, B. L. Evans and A. Gatherer, "Robust Learning-Based ML Detection for Massive MIMO Systems with One-Bit Quantized Signals," 2019 IEEE Global Communications Conference (GLOBECOM), 2019, pp. 1-6, doi: 10.1109/GLOBECOM38437.2019.9013332.

https://github.com/Yunseong-Cho/LearningML

[xiangli-bjtu]

Lee M, Yu G, Li G Y. Graph Embedding-Based Wireless Link Scheduling With Few Training Samples[J]. IEEE Transactions on Wireless Communications, 2020, 20(4): 2282-2294.

https://github.com/mengyuan-lee/graph_embedding_link_scheduling

[ruihuili]

Rui Li, Ondrej Bohdal, Rajesh K. Mishra, Hyeji Kim, Da Li, Nicholas Donald Lane, and Timothy Hospedales. "A Channel Coding Benchmark for Meta-Learning." NeurIPS 2021 Datasets and Benchmarks Track

https://openreview.net/forum?id=DjzPaX8AT0z
https://github.com/ruihuili/MetaCC

[linkpark]

J. Wang, J.Hu, G. Min, W. Zhan, A. Y. Zomaya, and N. Georgalas, "Dependent Task Offloading for Edge Computing based on Deep Reinforcement Learning." IEEE Transactions on Computers, 2021.

https://ieeexplore.ieee.org/abstract/document/9627763
https://github.com/linkpark/RLTaskOffloading