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Found 3 papers, 1 papers with code
Towards Understanding and Improving GFlowNet Training
We investigate how to learn better flows, and propose (i) prioritized replay training of high-reward $x$, (ii) relative edge flow policy parametrization, and (iii) a novel guided trajectory balance objective, and show how it can solve a substructure credit assignment problem.
Conditional Diffusion with Less Explicit Guidance via Model Predictive Control
How much explicit guidance is necessary for conditional diffusion?
Trust in AI: Interpretability is not necessary or sufficient, while black-box interaction is necessary and sufficient
We clarify the role of interpretability in trust with a ladder of model access.
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