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causal discovery

459 papers

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Also known as

CD

Co-occurring keywords

causal inference (1619) graphical model (863) directed acyclic graph (242) causal graph (137) structure learning (341) causal structure (87) structural equation model (77) latent variable (541) causal structure learning (63) time series (434)

Papers

Higher Order Kernel Mean Embeddings to Capture Filtrations of Stochastic Processes NIPS 2021
Learning latent causal graphs via mixture oracles NIPS 2021
BCD Nets: Scalable Variational Approaches for Bayesian Causal Discovery NIPS 2021
DiBS: Differentiable Bayesian Structure Learning NIPS 2021
Iterative Causal Discovery in the Possible Presence of Latent Confounders and Selection Bias NIPS 2021
Collaborative Causal Discovery with Atomic Interventions NIPS 2021
Reliable Causal Discovery with Improved Exact Search and Weaker Assumptions NIPS 2021
Identification of Partially Observed Linear Causal Models: Graphical Conditions for the Non-Gaussian and Heterogeneous Cases NIPS 2021
Beware of the Simulated DAG! Causal Discovery Benchmarks May Be Easy to Game NIPS 2021
Discovering Fully Oriented Causal Networks AAAI 2021
Statistical Undecidability in Linear, Non-Gaussian Causal Models in the Presence of Latent Confounders NIPS 2021
Actively Identifying Causal Effects with Latent Variables Given Only Response Variable Observable NIPS 2021
Causal additive models with unobserved variables UAI 2021
A weaker faithfulness assumption based on triple interactions UAI 2021
Kernel-based Approach for Learning Causal Graphs from Mixed Data PGM 2020
Robust contrastive learning and nonlinear ICA in the presence of outliers UAI 2020
Differentiable Causal Backdoor Discovery AISTATS 2020
RCD: Repetitive causal discovery of linear non-Gaussian acyclic models with latent confounders AISTATS 2020
Towards Scalable Bayesian Learning of Causal DAGs NIPS 2020
algcomparison: Comparing the Performance of Graphical Structure Learning Algorithms with TETRAD JMLR 2020
Bayesian Causal Structural Learning with Zero-Inflated Poisson Bayesian Networks NIPS 2020
Switching Regression Models and Causal Inference in the Presence of Discrete Latent Variables JMLR 2020
Causal Discovery Toolbox: Uncovering causal relationships in Python JMLR 2020
Recovering Causal Structures from Low-Order Conditional Independencies AAAI 2020
Differentiable Causal Discovery from Interventional Data NIPS 2020