79 citations · 139 across the 3 of their papers we have counts for
3 papers
stat.ML2019★ 41 cited
Stein Variational Gradient Descent With Matrix-Valued Kernels
Dilin Wang, Ziyang Tang, Chandrajit Bajaj +1
Stein variational gradient descent (SVGD) is a particle-based inference algorithm that leverages gradient information for efficient approximate inference. In this work, we enhance…
cs.LG2019★ 19 cited
Splitting Steepest Descent for Growing Neural Architectures
Qiang Liu, Lemeng Wu, Dilin Wang
We develop a progressive training approach for neural networks which adaptively grows the network structure by splitting existing neurons to multiple off-springs. By leveraging a f…
stat.ML2016★ 79 cited
Learning to Draw Samples: With Application to Amortized MLE for Generative Adversarial Learning
Dilin Wang, Qiang Liu
We propose a simple algorithm to train stochastic neural networks to draw samples from given target distributions for probabilistic inference. Our method is based on iteratively ad…