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Georgia Institute of Technology
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A single controller can now robustly learn stochastic transport across a range of initial distribution shifts, outperforming standard SB and noise augmentation on challenging tasks.
Entropic transport descent transforms particle-based variational inference by leveraging optimal transport principles, achieving superior performance in high-dimensional and multimodal distributions.
