351 citations · 1.2k across the 48 of their papers we have counts for
14 papers · 1 filter
Tracing the Propagation Path: A Flow Perspective of Representation Learning on Graphs
Menghan Wang, Kun Zhang, Gulin Li +2
Graph Convolutional Networks (GCNs) have gained significant developments in representation learning on graphs. However, current GCNs suffer from two common challenges: 1) GCNs are…
Transfer Learning-Based Outdoor Position Recovery with Telco Data
Yige Zhang, Aaron Yi Ding, Jorg Ott +4
Telecommunication (Telco) outdoor position recovery aims to localize outdoor mobile devices by leveraging measurement report (MR) data. Unfortunately, Telco position recovery requi…
Disentanglement Challenge: From Regularization to Reconstruction
Jie Qiao, Zijian Li, Boyan Xu +2
The challenge of learning disentangled representation has recently attracted much attention and boils down to a competition using a new real world disentanglement dataset (Gondal e…
Adversarial Orthogonal Regression: Two non-Linear Regressions for Causal Inference
M. Reza Heydari, Saber Salehkaleybar, Kun Zhang
We propose two nonlinear regression methods, named Adversarial Orthogonal Regression (AdOR) for additive noise models and Adversarial Orthogonal Structural Equation Model (AdOSE) f…
Likelihood-Free Overcomplete ICA and Applications in Causal Discovery
Chenwei Ding, Mingming Gong, Kun Zhang +1
Causal discovery witnessed significant progress over the past decades. In particular, many recent causal discovery methods make use of independent, non-Gaussian noise to achieve id…
Learning Linear Non-Gaussian Causal Models in the Presence of Latent Variables
Saber Salehkaleybar, AmirEmad Ghassami, Negar Kiyavash +1
We consider the problem of learning causal models from observational data generated by linear non-Gaussian acyclic causal models with latent variables. Without considering the effe…