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Methodology
← Core AI
Artificial Intelligence
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Causal Inference
3310 directly classified papers
Papers per year
2002: 1
2003: 2
2004: 1
2005: 2
2006: 7
2007: 6
2008: 9
2009: 9
2010: 15
2011: 8
2012: 15
2013: 32
2014: 16
2015: 28
2016: 39
2017: 62
2018: 98
2019: 201
2020: 277
2021: 372
2022: 426
2023: 511
2024: 601
2025: 389
2026: 183
Papers
Root Cause Identification for Collective Anomalies in Time Series given an Acyclic Summary Causal Graph with Loops
AISTATS 2023
Towards Balanced Representation Learning for Credit Policy Evaluation
AISTATS 2023
Stochastic Tree Ensembles for Estimating Heterogeneous Effects
AISTATS 2023
Learning Treatment Effects from Observational and Experimental Data
AISTATS 2023
Rank-Based Causal Discovery for Post-Nonlinear Models
AISTATS 2023
Nothing but Regrets — Privacy-Preserving Federated Causal Discovery
AISTATS 2023
Context-Specific Causal Discovery for Categorical Data Using Staged Trees
AISTATS 2023
Compositional Probabilistic and Causal Inference using Tractable Circuit Models
AISTATS 2023
Efficient SAGE Estimation via Causal Structure Learning
AISTATS 2023
Understanding the Impact of Competing Events on Heterogeneous Treatment Effect Estimation from Time-to-Event Data
AISTATS 2023
ViT-CX: Causal Explanation of Vision Transformers
IJCAI 2023
Sequential Recommendation with Probabilistic Logical Reasoning
IJCAI 2023
Disentanglement of Latent Representations via Causal Interventions
IJCAI 2023
Formal Explanations of Neural Network Policies for Planning
IJCAI 2023
Learning Causal Effects on Hypergraphs (Extended Abstract)
IJCAI 2023
Inference for a Large Directed Acyclic Graph with Unspecified Interventions
JMLR 2023
Learning Optimal Group-structured Individualized Treatment Rules with Many Treatments
JMLR 2023
Evaluating Instrument Validity using the Principle of Independent Mechanisms
JMLR 2023
Clustering and Structural Robustness in Causal Diagrams
JMLR 2023
Polynomial-Time Algorithms for Counting and Sampling Markov Equivalent DAGs with Applications
JMLR 2023
Augmented Transfer Regression Learning with Semi-non-parametric Nuisance Models
JMLR 2023
High-Dimensional Inference for Generalized Linear Models with Hidden Confounding
JMLR 2023
Causal Bandits for Linear Structural Equation Models
JMLR 2023
A Unified Experiment Design Approach for Cyclic and Acyclic Causal Models
JMLR 2023
Set-valued Classification with Out-of-distribution Detection for Many Classes
JMLR 2023
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