22 citations · 109 across the 34 of their papers we have counts for
Showing 2019Show all
3 papers · 1 filter
q-fin.RM2019★ 3 cited
Online Quantification of Input Model Uncertainty by Two-Layer Importance Sampling
Tianyi Liu, Enlu Zhou
Stochastic simulation has been widely used to analyze the performance of complex stochastic systems and facilitate decision making in those systems. Stochastic simulation is driven…
cs.LG2019★ 22 cited
Towards Understanding the Importance of Shortcut Connections in Residual Networks
Tianyi Liu, Minshuo Chen, Mo Zhou +3
Residual Network (ResNet) is undoubtedly a milestone in deep learning. ResNet is equipped with shortcut connections between layers, and exhibits efficient training using simple fir…
cs.LG2019★ 14 cited
Towards Understanding the Importance of Noise in Training Neural Networks
Mo Zhou, Tianyi Liu, Yan Li +3
Numerous empirical evidence has corroborated that the noise plays a crucial rule in effective and efficient training of neural networks. The theory behind, however, is still largel…