Nvidia Flare: Limitations and Potentials

I am interested in understanding the limitations of Nvidia Flare. I’m aware that it supports several frameworks, such as PyTorch, TensorFlow, Numpy, or MONAI. I am wondering if any model built using these frameworks would be able to function in a federated manner. Is there a particular subset of models that would be better suited for use in this platform?

Moreover, I relatively sure that I can construct models such as neural networks, logistic regression, linear regression, support vector machines, k-means, XGBoost, and random forests using Nvidia Flare. However, I am curious about the feasibility of implementing other models, such as Naive Bayes, decision trees, and gradient boosting. Would these models also be compatible with Nvidia Flare?

Thanks in advance!