4 citations · 6 across the 4 of their papers we have counts for
4 papers
Using causal inference to avoid fallouts in data-driven parametric analysis: a case study in the architecture, engineering, and construction industry
Xia Chen, Ruiji Sun, Ueli Saluz +2
The decision-making process in real-world implementations has been affected by a growing reliance on data-driven models. We investigated the synergetic pattern between the data-dri…
Utilizing Domain Knowledge: Robust Machine Learning for Building Energy Prediction with Small, Inconsistent Datasets
Xia Chen, Manav Mahan Singh, Philipp Geyer
The demand for a huge amount of data for machine learning (ML) applications is currently a bottleneck in an empirically dominated field. We propose a method to combine prior knowle…
A novel approach of empirical likelihood with massive data
Yang Liu, Xia Chen, Wei-min Yang
In this paper, we propose a novel approach for tackling the obstacles of empirical likelihood in the face of massive data, which is called split sample mean empirical likelihood (S…
Dual Domain-Adversarial Learning for Audio-Visual Saliency Prediction
Yingzi Fan, Longfei Han, Yue Zhang +3
Both visual and auditory information are valuable to determine the salient regions in videos. Deep convolution neural networks (CNN) showcase strong capacity in coping with the aud…