24 citations · 52 across the 9 of their papers we have counts for
4 papers · 1 filter
Weakly Supervised Disentangled Generative Causal Representation Learning
Xinwei Shen, Furui Liu, Hanze Dong +3
This paper proposes a Disentangled gEnerative cAusal Representation (DEAR) learning method under appropriate supervised information. Unlike existing disentanglement methods that en…
Surprise sampling: improving and extending the local case-control sampling
Xinwei Shen, Kani Chen, Wen Yu
Fithian and Hastie (2014) proposed a new sampling scheme called local case-control (LCC) sampling that achieves stability and efficiency by utilizing a clever adjustment pertained…
CausalVAE: Structured Causal Disentanglement in Variational Autoencoder
Mengyue Yang, Furui Liu, Zhitang Chen +3
Learning disentanglement aims at finding a low dimensional representation which consists of multiple explanatory and generative factors of the observational data. The framework of…
Bidirectional Generative Modeling Using Adversarial Gradient Estimation
Xinwei Shen, Tong Zhang, Kani Chen
This paper considers the general -divergence formulation of bidirectional generative modeling, which includes VAE and BiGAN as special cases. We present a new optimization metho…