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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
Multi-task Causal Learning with Gaussian Processes
NIPS 2020
Domain Adaptation as a Problem of Inference on Graphical Models
NIPS 2020
Trialstreamer: Mapping and Browsing Medical Evidence in Real-Time
ACL 2020
A/B Testing in Dense Large-Scale Networks: Design and Inference
NIPS 2020
A causal view of compositional zero-shot recognition
NIPS 2020
Enhancing Question Answering by Injecting Ontological Knowledge through Regularization
EMNLP 2020
Probabilistic Case-based Reasoning for Open-World Knowledge Graph Completion
EMNLP 2020
Discourse structure interacts with reference but not syntax in neural language models
EMNLP 2020
Thinking Like a Skeptic: Defeasible Inference in Natural Language
EMNLP 2020
Biomedical Event Extraction with Hierarchical Knowledge Graphs
EMNLP 2020
Personalized Input-Output Hidden Markov Models for Disease Progression Modeling
MLHC 2020
A Causally Formulated Hazard Ratio Estimation through Backdoor Adjustment on Structural Causal Model
MLHC 2020
Causal Shapley Values: Exploiting Causal Knowledge to Explain Individual Predictions of Complex Models
NIPS 2020
Off-policy Policy Evaluation For Sequential Decisions Under Unobserved Confounding
NIPS 2020
Learning to search efficiently for causally near-optimal treatments
NIPS 2020
Fighting Copycat Agents in Behavioral Cloning from Observation Histories
NIPS 2020
Reasoning Over Semantic-Level Graph for Fact Checking
ACL 2020
Causal Imitation Learning With Unobserved Confounders
NIPS 2020
General Transportability of Soft Interventions: Completeness Results
NIPS 2020
Inverse Rational Control with Partially Observable Continuous Nonlinear Dynamics
NIPS 2020
Counterfactual Data Augmentation using Locally Factored Dynamics
NIPS 2020
Can Graph Neural Networks Count Substructures?
NIPS 2020
Bayesian Causal Structural Learning with Zero-Inflated Poisson Bayesian Networks
NIPS 2020
Causal analysis of Covid-19 Spread in Germany
NIPS 2020
Counterfactual Predictions under Runtime Confounding
NIPS 2020
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