Ignavier Ng

Learning General Causal Structures with Hidden Dynamic Process for Climate Analysis

Score-based Greedy Search for Structure Identification of Partially Observed Causal Models

Identifying Partially Observed Causal Models from Heterogeneous/Nonstationary Data

Attribute-Guided Image Generation with Causally Disentangled Representation

When Selection Meets Intervention: Additional Complexities in Causal Discovery

Latent Variable Causal Discovery under Selection Bias

Analytic DAG Constraints for Differentiable DAG Learning

Learning General Causal Structures with Hidden Dynamic Process for Climate Analysis

Differentiable Causal Discovery for Latent Hierarchical Causal Models

A Skewness-Based Criterion for Addressing Heteroscedastic Noise in Causal Discovery

A General Representation-Based Approach to Multi-Source Domain Adaptation

Permutation-based Rank Test in the Presence of Discretization and Application in Causal Discovery with Mixed Data

Revisiting Differentiable Structure Learning: Inconsistency of $\ell_1$ Penalty and Beyond

Permutation-based Rank Test in the Presence of Discretization and Application in Causal Discovery with Mixed Data

Synergy Between Sufficient Changes and Sparse Mixing Procedure for Disentangled Representation Learning

Identification of Nonparametric Dynamic Causal Model and Latent Process for Climate Analysis

Higher-Order Causal Structure Learning with Additive Models

Learning Identifiable Concepts for Compositional Image Generation