{"total":46,"rows":[{"id":"2203.16437","title":"Weakly supervised causal representation learning","created":"2022-03-30","cited_by_count":140,"area":null},{"id":"2305.19366","title":"Joint Bayesian Inference of Graphical Structure and Parameters with a Single Generative Flow Network","created":"2023-05-30","cited_by_count":50,"area":null},{"id":"2304.02146","title":"Structure Learning with Continuous Optimization: A Sober Look and Beyond","created":"2023-04-04","cited_by_count":36,"area":null},{"id":"2307.13917","title":"BayesDAG: Gradient-Based Posterior Inference for Causal Discovery","created":"2023-07-26","cited_by_count":33,"area":null},{"id":"2412.16577","title":"A Meta-Learning Approach to Bayesian Causal Discovery","created":"2024-12-21","cited_by_count":22,"area":null},{"id":"2402.18477","title":"Signature Kernel Conditional Independence Tests in Causal Discovery for Stochastic Processes","created":"2024-02-28","cited_by_count":18,"area":null},{"id":"2310.02895","title":"CoLiDE: Concomitant Linear DAG Estimation","created":"2023-10-04","cited_by_count":13,"area":null},{"id":"2410.05890","title":"Ordering-Based Causal Discovery for Linear and Nonlinear Relations","created":"2024-10-08","cited_by_count":13,"area":null},{"id":"2507.05526","title":"Estimating Interventional Distributions with Uncertain Causal Graphs through Meta-Learning","created":"2025-07-07","cited_by_count":13,"area":null},{"id":"2309.08406","title":"Constraint-Free Structure Learning with Smooth Acyclic Orientations","created":"2023-09-15","cited_by_count":10,"area":null},{"id":"2301.11898","title":"DAG Learning on the Permutahedron","created":"2023-01-27","cited_by_count":9,"area":null},{"id":"2305.15936","title":"Learning DAGs from Data with Few Root Causes","created":"2023-05-25","cited_by_count":8,"area":null},{"id":"2402.14781","title":"Effective Bayesian Causal Inference via Structural Marginalisation and Autoregressive Orders","created":"2024-02-22","cited_by_count":6,"area":null},{"id":"2210.13583","title":"Learning Latent Structural Causal Models","created":"2022-10-24","cited_by_count":5,"area":null},{"id":"2308.07480","title":"Order-based Structure Learning with Normalizing Flows","created":"2023-08-14","cited_by_count":5,"area":null},{"id":"2605.07204","title":"Arrow: A Foundation Model for Causal Discovery","created":"2026-05-08","cited_by_count":5,"area":null},{"id":"2402.02644","title":"Permutation-based Inference for Variational Learning of Directed Acyclic Graphs","created":"2024-02-04","cited_by_count":4,"area":null},{"id":"2405.15167","title":"ProDAG: Projected Variational Inference for Directed Acyclic Graphs","created":"2024-05-24","cited_by_count":4,"area":null},{"id":"2410.20089","title":"Sample Efficient Bayesian Learning of Causal Graphs from Interventions","created":"2024-10-26","cited_by_count":4,"area":null},{"id":"2208.14989","title":"Learning Multiscale Non-stationary Causal Structures","created":"2022-08-31","cited_by_count":3,"area":null},{"id":"2210.15353","title":"Learning Discrete Directed Acyclic Graphs via Backpropagation","created":"2022-10-27","cited_by_count":3,"area":null},{"id":"2302.09731","title":"CMVAE: Causal Meta VAE for Unsupervised Meta-Learning","created":"2023-02-20","cited_by_count":3,"area":null},{"id":"2310.13576","title":"Tree Search in DAG Space with Model-based Reinforcement Learning for Causal Discovery","created":"2023-10-20","cited_by_count":3,"area":null},{"id":"2502.10883","title":"Learning Identifiable Structures Helps Avoid Bias in DNN-based Supervised Causal Learning","created":"2025-02-15","cited_by_count":3,"area":null},{"id":"2306.01920","title":"Context-Aware Bayesian Network Actor-Critic Methods for Cooperative Multi-Agent Reinforcement Learning","created":"2023-06-02","cited_by_count":2,"area":null},{"id":"2510.06735","title":"Incorporating Expert Knowledge into Bayesian Causal Discovery of Mixtures of Directed Acyclic Graphs","created":"2025-10-08","cited_by_count":2,"area":null},{"id":"2603.20842","title":"A Knowledge-Informed Pretrained Model for Causal Discovery","created":"2026-03-21","cited_by_count":2,"area":null},{"id":"2605.23537","title":"Concomitant DAG Learning: On the Roles of Noise Adaptivity, Sparsity, and Non-negativity","created":"2026-05-22","cited_by_count":2,"area":null},{"id":"2207.05723","title":"Latent Variable Models for Bayesian Causal Discovery","created":"2022-07-12","cited_by_count":1,"area":null},{"id":"2312.05757","title":"Towards Human-like Perception: Learning Structural Causal Model in Heterogeneous Graph","created":"2023-12-10","cited_by_count":1,"area":null},{"id":"2407.04992","title":"Scalable Variational Causal Discovery Unconstrained by Acyclicity","created":"2024-07-06","cited_by_count":1,"area":null},{"id":"2410.19870","title":"Causal Order Discovery based on Monotonic SCMs","created":"2024-10-24","cited_by_count":1,"area":null},{"id":"2502.17030","title":"Your Assumed DAG is Wrong and Here's How To Deal With It","created":"2025-02-24","cited_by_count":1,"area":null},{"id":"2510.22298","title":"MetaCaDI: A Meta-Learning Framework for Causal Discovery from Multiple Environments with Unknown Interventions","created":"2025-10-25","cited_by_count":1,"area":null},{"id":"2512.11840","title":"Amortized Causal Discovery with Prior-Fitted Networks","created":"2025-12-03","cited_by_count":1,"area":null},{"id":"2310.16374","title":"Joint Distributional Learning via Cramer-Wold Distance","created":"2023-10-25","cited_by_count":0,"area":null},{"id":"2402.11124","title":"Implicit Causal Representation Learning via Switchable Mechanisms","created":"2024-02-16","cited_by_count":0,"area":null},{"id":"2406.15189","title":"Causal Learning in Biomedical Applications: Krebs Cycle as a Benchmark","created":"2024-06-21","cited_by_count":0,"area":null},{"id":"2512.22150","title":"Towards Unsupervised Causal Representation Learning via Latent Additive Noise Model Causal Autoencoders","created":"2025-12-15","cited_by_count":0,"area":null},{"id":"2604.04290","title":"DAGAF: A directed acyclic generative adversarial framework for joint structure learning and tabular data synthesis","created":"2026-04-05","cited_by_count":0,"area":null},{"id":"2606.03227","title":"Learning Temporal Causal Structure via Smooth Differentiable Optimization","created":"2026-06-02","cited_by_count":0,"area":null},{"id":"2606.06908","title":"polyDAG: Polynomial Acyclicity Constraints for Efficient Continuous Causal Discovery in Visual Semantic Graphs","created":"2026-06-05","cited_by_count":0,"area":null},{"id":"2607.22934","title":"Amortized Bayesian Causal Discovery of Extended Factor Graphs","created":"2026-07-24","cited_by_count":0,"area":null},{"id":"2608.04930","title":"SVI-DAG: A Structured Variational Inference Approach to Bayesian Causal Discovery","created":"2026-08-05","cited_by_count":0,"area":null},{"id":"2609.37122","title":"Learning the Structure of Triangular Transport Maps","created":"2026-09-29","cited_by_count":0,"area":null},{"id":"2610.09276","title":"CATune: Structural Constraint-Aware Bayesian Optimization for DBMS Configuration Tuning","created":"2026-10-07","cited_by_count":0,"area":null}],"next_cursor":null}