[AAAI 2023] iBaML

Implementation of AAAI 2023 paper “Scalable Bayesian Meta-Learning through Generalized Implicit Gradients”.

Codes tested under the following environment:

---

• PyTorch 1.9.1
• CuDNN 7.6.5
• Torchvision 0.10.1
• Torch-utils 0.1.2
• Torchmeta 1.8.0
• Pillow 9.2.0

Scripts for reproducing the reported results can be found in scripts.sh. Default experimental setups can be seen in main.py.

Citation

Y. Zhang, B. Li, S. Gao and G. B. Giannakis, "Scalable Bayesian Meta-Learning through Generalized Implicit Gradients," Proc. of 35th AAAI Conf. on Artificial Intelligence, Washington DC, February 7-14, 2023.

@inproceedings{iBaML, 
  title={Scalable Bayesian Meta-Learning through Generalized Implicit Gradients}, 
  volume={37}, 
  url={https://ojs.aaai.org/index.php/AAAI/article/view/26337}, 
  DOI={10.1609/aaai.v37i9.26337}, 
  number={9}, 
  booktitle={Proceedings of the AAAI Conference on Artificial Intelligence}, 
  author={Zhang, Yilang and Li, Bingcong and Gao, Shijian and Giannakis, Georgios B.}, 
  year={2023}, 
  month={Jun.}, 
  pages={11298-11306} 
}