From the 1 of 4 linked papers with an AI index.
8 citations · 16 across the 3 of their papers we have counts for
4 papers
GNet: A scalable and flexible Gaussian process network with nonparametric neurons
Mengyang Gu
The paper introduces GNet, a Gaussian process based neural network that uses nonparametric activation functions and a jointly inverse Kalman filter to enable scalable training and…
Scalable marginalization of correlated latent variables with applications to learning particle interaction kernels
Mengyang Gu, Xubo Liu, Xinyi Fang +1
Marginalization of latent variables or nuisance parameters is a fundamental aspect of Bayesian inference and uncertainty quantification. In this work, we focus on scalable marginal…
Fast Nonseparable Gaussian Stochastic Process with Application to Methylation Level Interpolation
Mengyang Gu, Yanxun Xu
Gaussian stochastic process (GaSP) has been widely used as a prior over functions due to its flexibility and tractability in modeling. However, the computational cost in evaluating…
RobustGaSP: Robust Gaussian Stochastic Process Emulation in R
Mengyang Gu, Jesús Palomo, James O. Berger
Gaussian stochastic process emulation is a powerful tool for approximating computationally intensive computer models. However, estimation of parameters in the GaSP emulator is a ch…