{"total":199,"rows":[{"id":"2102.13647","title":"Beware of the Simulated DAG! Causal Discovery Benchmarks May Be Easy To Game","created":"2021-02-26","cited_by_count":161,"area":null},{"id":"2107.10098","title":"Disentanglement via Mechanism Sparsity Regularization: A New Principle for Nonlinear ICA","created":"2021-07-21","cited_by_count":160,"area":null},{"id":"2202.13903","title":"Bayesian Structure Learning with Generative Flow Networks","created":"2022-02-28","cited_by_count":153,"area":null},{"id":"2209.11924","title":"Interventional Causal Representation Learning","created":"2022-09-24","cited_by_count":142,"area":null},{"id":"2203.16437","title":"Weakly supervised causal representation learning","created":"2022-03-30","cited_by_count":140,"area":null},{"id":"2105.11839","title":"DiBS: Differentiable Bayesian Structure Learning","created":"2021-05-25","cited_by_count":106,"area":null},{"id":"2306.00542","title":"Nonparametric Identifiability of Causal Representations from Unknown Interventions","created":"2023-06-01","cited_by_count":106,"area":null},{"id":"2107.00793","title":"The Causal-Neural Connection: Expressiveness, Learnability, and Inference","created":"2021-07-02","cited_by_count":98,"area":null},{"id":"2205.12934","title":"Amortized Inference for Causal Structure Learning","created":"2022-05-25","cited_by_count":90,"area":null},{"id":"2107.10483","title":"Efficient Neural Causal Discovery without Acyclicity Constraints","created":"2021-07-22","cited_by_count":82,"area":null},{"id":"2204.04875","title":"Learning to Induce Causal Structure","created":"2022-04-11","cited_by_count":68,"area":null},{"id":"2307.02390","title":"Causal Discovery with Language Models as Imperfect Experts","created":"2023-07-05","cited_by_count":64,"area":null},{"id":"2302.00615","title":"GFlowNets for AI-Driven Scientific Discovery","created":"2023-02-01","cited_by_count":63,"area":null},{"id":"2305.10032","title":"A Survey on Causal Discovery: Theory and Practice","created":"2023-05-17","cited_by_count":63,"area":null},{"id":"2111.15155","title":"gCastle: A Python Toolbox for Causal Discovery","created":"2021-11-30","cited_by_count":61,"area":null},{"id":"2206.02013","title":"Causal Discovery in Heterogeneous Environments Under the Sparse Mechanism Shift Hypothesis","created":"2022-06-04","cited_by_count":55,"area":null},{"id":"2206.06169","title":"Causal Representation Learning for Instantaneous and Temporal Effects in Interactive Systems","created":"2022-06-13","cited_by_count":51,"area":null},{"id":"2203.02016","title":"Interventions, Where and How? Experimental Design for Causal Models at Scale","created":"2022-03-03","cited_by_count":49,"area":null},{"id":"2203.08509","title":"Differentiable DAG Sampling","created":"2022-03-16","cited_by_count":47,"area":null},{"id":"2206.07824","title":"Large-Scale Differentiable Causal Discovery of Factor Graphs","created":"2022-06-15","cited_by_count":47,"area":null},{"id":"2206.01152","title":"Causal Structure Learning: a Combinatorial Perspective","created":"2022-06-02","cited_by_count":46,"area":null},{"id":"2102.05829","title":"Causal Inference for Time series Analysis: Problems, Methods and Evaluation","created":"2021-02-11","cited_by_count":42,"area":null},{"id":"2109.02429","title":"Learning Neural Causal Models with Active Interventions","created":"2021-09-06","cited_by_count":40,"area":null},{"id":"2306.09643","title":"BISCUIT: Causal Representation Learning from Binary Interactions","created":"2023-06-16","cited_by_count":38,"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":"2305.13341","title":"Discovering Causal Relations and Equations from Data","created":"2023-05-21","cited_by_count":36,"area":null},{"id":"2206.02063","title":"Active Bayesian Causal Inference","created":"2022-06-04","cited_by_count":35,"area":null},{"id":"2211.03553","title":"Learning Causal Representations of Single Cells via Sparse Mechanism Shift Modeling","created":"2022-11-07","cited_by_count":34,"area":null},{"id":"2110.09356","title":"Towards Federated Bayesian Network Structure Learning with Continuous Optimization","created":"2021-10-18","cited_by_count":31,"area":null},{"id":"2311.10263","title":"Stable Differentiable Causal Discovery","created":"2023-11-17","cited_by_count":31,"area":null},{"id":"2211.02763","title":"Bayesian learning of Causal Structure and Mechanisms with GFlowNets and Variational Bayes","created":"2022-11-04","cited_by_count":30,"area":null},{"id":"2210.17283","title":"CausalBench: A Large-scale Benchmark for Network Inference from Single-cell Perturbation Data","created":"2022-10-31","cited_by_count":29,"area":null},{"id":"2206.01665","title":"BaCaDI: Bayesian Causal Discovery with Unknown Interventions","created":"2022-06-03","cited_by_count":26,"area":null},{"id":"2307.01452","title":"Causal Reinforcement Learning: A Survey","created":"2023-07-04","cited_by_count":23,"area":null},{"id":"2102.10440","title":"Interventional Sum-Product Networks: Causal Inference with Tractable Probabilistic Models","created":"2021-02-20","cited_by_count":22,"area":null},{"id":"2205.13869","title":"MissDAG: Causal Discovery in the Presence of Missing Data with Continuous Additive Noise Models","created":"2022-05-27","cited_by_count":22,"area":null},{"id":"2203.02336","title":"Differentiable Causal Discovery Under Latent Interventions","created":"2022-03-04","cited_by_count":21,"area":null},{"id":"2209.06203","title":"Normalizing Flows for Interventional Density Estimation","created":"2022-09-13","cited_by_count":21,"area":null},{"id":"2402.01929","title":"Sample, estimate, aggregate: A recipe for causal discovery foundation models","created":"2024-02-02","cited_by_count":21,"area":null},{"id":"2212.04866","title":"Deep Learning of Causal Structures in High Dimensions","created":"2022-12-09","cited_by_count":20,"area":null},{"id":"2301.01849","title":"NODAGS-Flow: Nonlinear Cyclic Causal Structure Learning","created":"2023-01-04","cited_by_count":20,"area":null},{"id":"2310.17405","title":"Causal Modeling with Stationary Diffusions","created":"2023-10-26","cited_by_count":19,"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":"2112.03555","title":"FedDAG: Federated DAG Structure Learning","created":"2021-12-07","cited_by_count":17,"area":null},{"id":"2109.11990","title":"Optimization-based Causal Estimation from Heterogenous Environments","created":"2021-09-24","cited_by_count":16,"area":null},{"id":"2204.04606","title":"Towards efficient representation identification in supervised learning","created":"2022-04-10","cited_by_count":14,"area":null},{"id":"2310.02895","title":"CoLiDE: Concomitant Linear DAG Estimation","created":"2023-10-04","cited_by_count":13,"area":null},{"id":"2311.02221","title":"Structured Neural Networks for Density Estimation and Causal Inference","created":"2023-11-03","cited_by_count":13,"area":null},{"id":"2404.14786","title":"RealTCD: Temporal Causal Discovery from Interventional Data with Large Language Model","created":"2024-04-23","cited_by_count":13,"area":null},{"id":"2410.22729","title":"Identifying Drift, Diffusion, and Causal Structure from Temporal Snapshots","created":"2024-10-30","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":"2211.14897","title":"Characterization and Greedy Learning of Gaussian Structural Causal Models under Unknown Interventions","created":"2022-11-27","cited_by_count":12,"area":null},{"id":"2403.09300","title":"Recursive Causal Discovery","created":"2024-03-14","cited_by_count":12,"area":null},{"id":"2406.13371","title":"Identifiable Causal Representation Learning: Unsupervised, Multi-View, and Multi-Environment","created":"2024-06-19","cited_by_count":12,"area":null},{"id":"2407.16067","title":"LCA-on-the-Line: Benchmarking Out-of-Distribution Generalization with Class Taxonomies","created":"2024-07-22","cited_by_count":12,"area":null},{"id":"2410.15939","title":"CausalGraph2LLM: Evaluating LLMs for Causal Queries","created":"2024-10-21","cited_by_count":12,"area":null},{"id":"2207.08457","title":"A Meta-Reinforcement Learning Algorithm for Causal Discovery","created":"2022-07-18","cited_by_count":11,"area":null},{"id":"2405.16924","title":"Demystifying amortized causal discovery with transformers","created":"2024-05-27","cited_by_count":11,"area":null},{"id":"2503.01139","title":"Can Large Language Models Help Experimental Design for Causal Discovery?","created":"2025-03-03","cited_by_count":11,"area":null},{"id":"2107.10703","title":"Typing assumptions improve identification in causal discovery","created":"2021-07-22","cited_by_count":10,"area":null},{"id":"2111.07512","title":"Scalable Intervention Target Estimation in Linear Models","created":"2021-11-15","cited_by_count":10,"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":"2407.18755","title":"Score matching through the roof: linear, nonlinear, and latent variables causal discovery","created":"2024-07-26","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":"2206.04620","title":"On the Generalization and Adaption Performance of Causal Models","created":"2022-06-09","cited_by_count":8,"area":null},{"id":"2502.19551","title":"Extremely Greedy Equivalence Search","created":"2025-02-26","cited_by_count":8,"area":null},{"id":"2308.15395","title":"The CausalBench challenge: A machine learning contest for gene network inference from single-cell perturbation data","created":"2023-08-29","cited_by_count":7,"area":null},{"id":"2312.06091","title":"Learning Unknown Intervention Targets in Structural Causal Models from Heterogeneous Data","created":"2023-12-11","cited_by_count":7,"area":null},{"id":"2407.16975","title":"On the Parameter Identifiability of Partially Observed Linear Causal Models","created":"2024-07-24","cited_by_count":7,"area":null},{"id":"2410.06163","title":"Markov Equivalence and Consistency in Differentiable Structure Learning","created":"2024-10-08","cited_by_count":7,"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":"2406.09177","title":"Scalable and Flexible Causal Discovery with an Efficient Test for Adjacency","created":"2024-06-13","cited_by_count":6,"area":null},{"id":"2408.16218","title":"Large-Scale Targeted Cause Discovery via Learning from Simulated Data","created":"2024-08-29","cited_by_count":6,"area":null},{"id":"2410.21141","title":"LLM-initialized Differentiable Causal Discovery","created":"2024-10-28","cited_by_count":6,"area":null},{"id":"2501.02409","title":"Interpretable Neural ODEs for Gene Regulatory Network Discovery under Perturbations","created":"2025-01-05","cited_by_count":6,"area":null},{"id":"2602.08629","title":"CauScale: Neural Causal Discovery at Scale","created":"2026-02-09","cited_by_count":6,"area":null},{"id":"2106.02835","title":"On the Role of Entropy-based Loss for Learning Causal Structures with Continuous Optimization","created":"2021-06-05","cited_by_count":5,"area":null},{"id":"2210.13583","title":"Learning Latent Structural Causal Models","created":"2022-10-24","cited_by_count":5,"area":null},{"id":"2211.13715","title":"Trust Your $\\nabla$: Gradient-based Intervention Targeting for Causal Discovery","created":"2022-11-24","cited_by_count":5,"area":null},{"id":"2306.17361","title":"iSCAN: Identifying Causal Mechanism Shifts among Nonlinear Additive Noise Models","created":"2023-06-30","cited_by_count":5,"area":null},{"id":"2405.18314","title":"Deriving Causal Order from Single-Variable Interventions: Guarantees & Algorithm","created":"2024-05-28","cited_by_count":5,"area":null},{"id":"2410.07013","title":"Causal Representation Learning in Temporal Data via Single-Parent Decoding","created":"2024-10-09","cited_by_count":5,"area":null},{"id":"2505.20628","title":"Position: Adopt Constraints Over Fixed Penalties in Deep Learning","created":"2025-05-27","cited_by_count":5,"area":null},{"id":"2506.09891","title":"Causal Climate Emulation with Bayesian Filtering","created":"2025-06-11","cited_by_count":5,"area":null},{"id":"2511.07236","title":"Does TabPFN Understand Causal Structures?","created":"2025-11-10","cited_by_count":5,"area":null},{"id":"2110.02395","title":"Causal Explanations of Structural Causal Models","created":"2021-10-05","cited_by_count":4,"area":null},{"id":"2310.14246","title":"Shortcuts for causal discovery of nonlinear models by score matching","created":"2023-10-22","cited_by_count":4,"area":null},{"id":"2405.07220","title":"On Discovery of Local Independence over Continuous Variables via Neural Contextual Decomposition","created":"2024-05-12","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":"2405.20448","title":"Knockout: A simple way to handle missing inputs","created":"2024-05-30","cited_by_count":4,"area":null},{"id":"2406.10419","title":"Learning Flexible Time-windowed Granger Causality Integrating Heterogeneous Interventional Time Series Data","created":"2024-06-14","cited_by_count":4,"area":null},{"id":"2408.02679","title":"Visual Analysis of Multi-outcome Causal Graphs","created":"2024-07-31","cited_by_count":4,"area":null},{"id":"2410.23862","title":"$\\psi$DAG: Projected Stochastic Approximation Iteration for DAG Structure Learning","created":"2024-10-31","cited_by_count":4,"area":null},{"id":"2411.14003","title":"Generative Intervention Models for Causal Perturbation Modeling","created":"2024-11-21","cited_by_count":4,"area":null},{"id":"2502.16056","title":"Since Faithfulness Fails: The Performance Limits of Neural Causal Discovery","created":"2025-02-22","cited_by_count":4,"area":null},{"id":"2508.08450","title":"Differentiable Cyclic Causal Discovery Under Unmeasured Confounders","created":"2025-08-11","cited_by_count":4,"area":null},{"id":"2510.12503","title":"The Robustness of Differentiable Causal Discovery in Misspecified Scenarios","created":"2025-10-14","cited_by_count":4,"area":null},{"id":"2606.19610","title":"Latent Confounded Causal Discovery via Lie Bracket Geometry","created":"2026-06-17","cited_by_count":4,"area":null},{"id":"2209.02946","title":"On the Sparse DAG Structure Learning Based on Adaptive Lasso","created":"2022-09-07","cited_by_count":3,"area":null},{"id":"2304.05823","title":"DiscoGen: Learning to Discover Gene Regulatory Networks","created":"2023-04-12","cited_by_count":3,"area":null}],"next_cursor":"100"}