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Statistical Divergences

2024

On Divergence Measures for Training GFlowNets

·274 words
Tiago Da Silva Eliezer De Souza Da Silva Diego Mesquita Publication Conference NeurIPS Deep Generative Models Statistical Divergences Variational Inference Generative Flow Networks

Novel approach to training Generative Flow Networks (GFlowNets) by minimizing divergence measures such as Renyi-$\alpha$, Tsallis-$\alpha$, and Kullback-Leibler (KL) divergences. Stochastic gradient estimators using variance reduction techniques leads to faster and stabler training.