78 citations · 280 across the 20 of their papers we have counts for
6 papers · 1 filter
Beta-VAE has 2 Behaviors: PCA or ICA?
Zhouzheng Li, Hao Liu
Beta-VAE is a very classical model for disentangled representation learning, the use of an expanding bottleneck that allow information into the decoder gradually is key to represen…
Out-of-distribution Prediction with Invariant Risk Minimization: The Limitation and An Effective Fix
Ruocheng Guo, Pengchuan Zhang, Hao Liu +1
This work considers the out-of-distribution (OOD) prediction problem where (1)~the training data are from multiple domains and (2)~the test domain is unseen in the training. DNNs f…
Disentangling Observed Causal Effects from Latent Confounders using Method of Moments
Anqi Liu, Hao Liu, Tongxin Li +3
Discovering the complete set of causal relations among a group of variables is a challenging unsupervised learning problem. Often, this challenge is compounded by the fact that the…
Doubly Robust Off-Policy Learning on Low-Dimensional Manifolds by Deep Neural Networks
Minshuo Chen, Hao Liu, Wenjing Liao +1
Causal inference explores the causation between actions and the consequent rewards on a covariate set. Recently deep learning has achieved a remarkable performance in causal infere…
Triply Robust Off-Policy Evaluation
Anqi Liu, Hao Liu, Anima Anandkumar +1
We propose a robust regression approach to off-policy evaluation (OPE) for contextual bandits. We frame OPE as a covariate-shift problem and leverage modern robust regression tools…
Triangle Generative Adversarial Networks
Zhe Gan, Liqun Chen, Weiyao Wang +5
A Triangle Generative Adversarial Network (-GAN) is developed for semi-supervised cross-domain joint distribution matching, where the training data consists of samples from each…