Cover Image

Differentiable Causal Discovery For Latent Hierarchical Causal Models

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Prashant, Parjanya, Ng, Ignavier, Zhang, Kun, Huang, Biwei
Format:	Preprint
Published:	2024
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Latent Variable Causal Discovery under Selection Bias
by: Dai, Haoyue, et al.
Published: (2025)

Federated Causal Discovery from Heterogeneous Data
by: Li, Loka, et al.
Published: (2024)

Revisiting Differentiable Structure Learning: Inconsistency of $\ell_1$ Penalty and Beyond
by: Jin, Kaifeng, et al.
Published: (2024)

Structure Learning with Continuous Optimization: A Sober Look and Beyond
by: Ng, Ignavier, et al.
Published: (2023)

A Skewness-Based Criterion for Addressing Heteroscedastic Noise in Causal Discovery
by: Lin, Yingyu, et al.
Published: (2024)

Local Causal Discovery with Linear non-Gaussian Cyclic Models
by: Dai, Haoyue, et al.
Published: (2024)

On the Parameter Identifiability of Partially Observed Linear Causal Models
by: Dong, Xinshuai, et al.
Published: (2024)

Causal Representation Learning from Multiple Distributions: A General Setting
by: Zhang, Kun, et al.
Published: (2024)

Higher-Order Causal Structure Learning with Additive Models
by: Enouen, James, et al.
Published: (2025)

When Selection Meets Intervention: Additional Complexities in Causal Discovery
by: Dai, Haoyue, et al.
Published: (2025)

Causal-learn: Causal Discovery in Python
by: Zheng, Yujia, et al.
Published: (2023)

Causal Representation Learning from General Environments under Nonparametric Mixing
by: Ng, Ignavier, et al.
Published: (2026)

Identifying Weight-Variant Latent Causal Models
by: Liu, Yuhang, et al.
Published: (2022)

Causal Structure Learning in Hawkes Processes with Complex Latent Confounder Networks
by: Jin, Songyao, et al.
Published: (2025)

Learning General Causal Structures with Hidden Dynamic Process for Climate Analysis
by: Fu, Minghao, et al.
Published: (2025)

Permutation-Based Rank Test in the Presence of Discretization and Application in Causal Discovery with Mixed Data
by: Dong, Xinshuai, et al.
Published: (2025)

Score-based Greedy Search for Structure Identification of Partially Observed Linear Causal Models
by: Dong, Xinshuai, et al.
Published: (2025)

Identifiable Latent Polynomial Causal Models Through the Lens of Change
by: Liu, Yuhang, et al.
Published: (2023)

A Fast Kernel-based Conditional Independence test with Application to Causal Discovery
by: Schacht, Oliver, et al.
Published: (2025)

Optimal Kernel Choice for Score Function-based Causal Discovery
by: Wang, Wenjie, et al.
Published: (2024)

Reinforcement Learning for Causal Discovery without Acyclicity Constraints
by: Duong, Bao, et al.
Published: (2024)

Gene Regulatory Network Inference in the Presence of Dropouts: a Causal View
by: Dai, Haoyue, et al.
Published: (2024)

Generalized Independent Noise Condition for Estimating Causal Structure with Latent Variables
by: Xie, Feng, et al.
Published: (2023)

Analytic DAG Constraints for Differentiable DAG Learning
by: Zhang, Zhen, et al.
Published: (2025)

Learning Discrete Concepts in Latent Hierarchical Models
by: Kong, Lingjing, et al.
Published: (2024)

On the Identifiability of Nonlinear ICA: Sparsity and Beyond
by: Zheng, Yujia, et al.
Published: (2022)

Beyond DAGs: A Latent Partial Causal Model for Multimodal Learning
by: Liu, Yuhang, et al.
Published: (2024)

Temporal Latent Variable Structural Causal Model for Causal Discovery under External Interferences
by: Cai, Ruichu, et al.
Published: (2025)

Causal Representation Meets Stochastic Modeling under Generic Geometry
by: Ren, Jiaxu, et al.
Published: (2026)

Stable Differentiable Causal Discovery
by: Nazaret, Achille, et al.
Published: (2023)

Transformer Is Inherently a Causal Learner
by: Wang, Xinyue, et al.
Published: (2026)

On the Identifiability of Sparse ICA without Assuming Non-Gaussianity
by: Ng, Ignavier, et al.
Published: (2024)

Scalable Differentiable Causal Discovery in the Presence of Latent Confounders with Skeleton Posterior (Extended Version)
by: Ma, Pingchuan, et al.
Published: (2024)

LLM-initialized Differentiable Causal Discovery
by: Kampani, Shiv, et al.
Published: (2024)

Efficient Differentiable Discovery of Causal Order
by: Chevalley, Mathieu, et al.
Published: (2024)

Relational Causal Discovery with Latent Confounders
by: Negro, Matteo, et al.
Published: (2025)

KAIROS: Scalable Model-Agnostic Data Valuation
by: Zhu, Jiongli, et al.
Published: (2025)

Large Causal Models for Temporal Causal Discovery
by: Kougioulis, Nikolaos, et al.
Published: (2026)

CausalEvolve: Towards Open-Ended Discovery with Causal Scratchpad
by: Chen, Yongqiang, et al.
Published: (2026)

A Knowledge-Informed Pretrained Model for Causal Discovery
by: Xu, Wenbo, et al.
Published: (2026)