55 citations · 55 across the 1 of their papers we have counts for
4 papers
On the Role of Sparsity and DAG Constraints for Learning Linear DAGs
Ignavier Ng, AmirEmad Ghassami, Kun Zhang
Learning graphical structures based on Directed Acyclic Graphs (DAGs) is a challenging problem, partly owing to the large search space of possible graphs. A recent line of work for…
A Graph Autoencoder Approach to Causal Structure Learning
Ignavier Ng, Shengyu Zhu, Zhitang Chen +1
Causal structure learning has been a challenging task in the past decades and several mainstream approaches such as constraint- and score-based methods have been studied with theor…
Causal Discovery with Reinforcement Learning
Shengyu Zhu, Ignavier Ng, Zhitang Chen
Discovering causal structure among a set of variables is a fundamental problem in many empirical sciences. Traditional score-based casual discovery methods rely on various local he…
Lipizzaner: A System That Scales Robust Generative Adversarial Network Training
Tom Schmiedlechner, Ignavier Ng Zhi Yong, Abdullah Al-Dujaili +2
GANs are difficult to train due to convergence pathologies such as mode and discriminator collapse. We introduce Lipizzaner, an open source software system that allows machine lear…