2 citations · 2 across the 8 of their papers we have counts for
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Controlling Dependence in Implicit Generative Models via Spread Mutual Information
Jiahao Yu, Song Liu, José Miguel Hernández-Lobato +1
Mutual information (MI) provides an objective for suppressing or encouraging statistical dependence in implicit generative models. However, direct MI evaluation is challenging in i…
Bridging Stochastic Flow Maps and Boltzmann Generators with Normalizing Flows
Louis Grenioux, RuiKang OuYang, Luhuan Wu
Generating independent, equilibrium samples of molecular systems at scale remains a central obstacle in computational statistical mechanics. Boltzmann Generators address this by pa…
Stochastic Interpolants in Hilbert Spaces
James Boran Yu, RuiKang OuYang, Julien Horwood +1
Although diffusion models have successfully extended to function-valued data, stochastic interpolants -- which offer a flexible way to bridge arbitrary distributions -- remain limi…
A Diffusive Classification Loss for Learning Energy-based Generative Models
RuiKang OuYang, Louis Grenioux, José Miguel Hernández-Lobato
Score-based generative models have recently achieved remarkable success. While they are usually parameterized by the score, an alternative way is to use a series of time-dependent…