Research Explorer
Papers
Trends
Conferences
Explore
Authors
Topics
Keywords
Papers
Trends
Conferences
Explore
Authors
Topics
Keywords
Achievements
About
Methodology
← Reasoning
Knowledge & Reasoning
›
Reasoning
›
Causal Inference
934 directly classified papers
Papers per year
2006: 3
2007: 2
2008: 9
2009: 5
2010: 8
2011: 5
2012: 4
2013: 11
2014: 7
2015: 11
2016: 18
2017: 14
2018: 32
2019: 69
2020: 91
2021: 82
2022: 129
2023: 158
2024: 160
2025: 107
2026: 9
Papers
Generated Knowledge Prompting for Commonsense Reasoning
ACL 2022
Relevant CommonSense Subgraphs for “What if...” Procedural Reasoning
ACL 2022
CICERO: A Dataset for Contextualized Commonsense Inference in Dialogues
ACL 2022
Context-aware Information-theoretic Causal De-biasing for Interactive Sequence Labeling
EMNLP 2022
OrphicX: A Causality-Inspired Latent Variable Model for Interpreting Graph Neural Networks
CVPR 2022
Causality Inspired Representation Learning for Domain Generalization
CVPR 2022
Causal Discovery in Linear Latent Variable Models Subject to Measurement Error
NIPS 2022
Counterfactual Fairness with Partially Known Causal Graph
NIPS 2022
MissDAG: Causal Discovery in the Presence of Missing Data with Continuous Additive Noise Models
NIPS 2022
Sample Constrained Treatment Effect Estimation
NIPS 2022
Latent Hierarchical Causal Structure Discovery with Rank Constraints
NIPS 2022
Debiased Causal Tree: Heterogeneous Treatment Effects Estimation with Unmeasured Confounding
NIPS 2022
Staggered Rollout Designs Enable Causal Inference Under Interference Without Network Knowledge
NIPS 2022
Bivariate Causal Discovery for Categorical Data via Classification with Optimal Label Permutation
NIPS 2022
Causal Discovery in Heterogeneous Environments Under the Sparse Mechanism Shift Hypothesis
NIPS 2022
Deep Multi-Modal Structural Equations For Causal Effect Estimation With Unstructured Proxies
NIPS 2022
Conditional Independence Testing with Heteroskedastic Data and Applications to Causal Discovery
NIPS 2022
Large-Scale Differentiable Causal Discovery of Factor Graphs
NIPS 2022
Interventions, Where and How? Experimental Design for Causal Models at Scale
NIPS 2022
An Adaptive Kernel Approach to Federated Learning of Heterogeneous Causal Effects
NIPS 2022
Disentangling Causal Effects from Sets of Interventions in the Presence of Unobserved Confounders
NIPS 2022
Causal Discovery in Hawkes Processes by Minimum Description Length
AAAI 2022
A Hybrid Causal Structure Learning Algorithm for Mixed-Type Data
AAAI 2022
Deconfounded Visual Grounding
AAAI 2022
On Testing for Discrimination Using Causal Models
AAAI 2022
<
1
…
20
21
22
…
38
>