# Personalized Bayesian Federated Learning with Wasserstein Barycenter Aggregation

We provide the code for our method using a DNN on the MNIST dataset.

## Downloading dependencies

```
pip3 install -r requirements.txt  
```

## Run on real federated datasets


According to the following code, the results of MNIST on 50 clients can be reproduced. For 100 clients, set k to 20.

python /mnt/New/main_new.py --dataset MNIST --num_svgd 48 --num_devices 50 --M 10 --k 10 --batch_size 128 --alpha_ada 0.0004 --epsilon_ada 0.000000001 --betta 0.9
