2 citations · 4 across the 3 of their papers we have counts for
3 papers
cs.LG2022★ 2 cited
Independence Testing-Based Approach to Causal Discovery under Measurement Error and Linear Non-Gaussian Models
Haoyue Dai, Peter Spirtes, Kun Zhang
Causal discovery aims to recover causal structures generating the observational data. Despite its success in certain problems, in many real-world scenarios the observed variables a…
cs.LG2021★ 1 cited
ML4C: Seeing Causality Through Latent Vicinity
Haoyue Dai, Rui Ding, Yuanyuan Jiang +2
Supervised Causal Learning (SCL) aims to learn causal relations from observational data by accessing previously seen datasets associated with ground truth causal relations. This pa…
cs.CV2020★ 1 cited
What do CNN neurons learn: Visualization & Clustering
Haoyue Dai
In recent years convolutional neural networks (CNN) have shown striking progress in various tasks. However, despite the high performance, the training and prediction process remain…