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20202024
most citedAn empirical study of the effect of background data size on the stability of SHapley Additive exPlanations (SHAP) for deep learning models

15 citations · 20 across the 10 of their papers we have counts for

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stat.CO2021

Convergence Analysis of Schr{ö}dinger-F{ö}llmer Sampler without Convexity

Yuling Jiao, Lican Kang, Yanyan Liu +1

Schrödinger-Föllmer sampler (SFS) is a novel and efficient approach for sampling from possibly unnormalized distributions without ergodicity. SFS is based on the Euler-Maruyama dis…

stat.CO2021★ 5 cited

Schr{ö}dinger-F{ö}llmer Sampler: Sampling without Ergodicity

Jian Huang, Yuling Jiao, Lican Kang +3

Sampling from probability distributions is an important problem in statistics and machine learning, specially in Bayesian inference when integration with respect to posterior distr…