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← Core AI
Artificial Intelligence
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Core AI
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Causal Inference
3,310 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
Learning good interventions in causal graphs via covering
UAI 2023
Counting Background Knowledge Consistent Markov Equivalent Directed Acyclic Graphs
UAI 2023
Learning Nonlinear Causal Effect via Kernel Anchor Regression
UAI 2023
Mixture of Normalizing Flows for European Option Pricing
UAI 2023
Surface Normal Estimation From Optimized and Distributed Light Sources Using DNN-Based Photometric Stereo
WACV 2023
Neural Implicit Representations for Physical Parameter Inference From a Single Video
WACV 2023
GeoFill: Reference-Based Image Inpainting With Better Geometric Understanding
WACV 2023
Treatment Learning Causal Transformer for Noisy Image Classification
WACV 2023
More Knowledge, Less Bias: Unbiasing Scene Graph Generation With Explicit Ontological Adjustment
WACV 2023
Markovian Interference in Experiments
NIPS 2022
Off-Policy Evaluation for Episodic Partially Observable Markov Decision Processes under Non-Parametric Models
NIPS 2022
Causal Discovery in Linear Latent Variable Models Subject to Measurement Error
NIPS 2022
Environment Diversification with Multi-head Neural Network for Invariant Learning
NIPS 2022
Neural-Symbolic Entangled Framework for Complex Query Answering
NIPS 2022
Causality Preserving Chaotic Transformation and Classification using Neurochaos Learning
NIPS 2022
Debiased Machine Learning without Sample-Splitting for Stable Estimators
NIPS 2022
Online Reinforcement Learning for Mixed Policy Scopes
NIPS 2022
Causal Identification under Markov equivalence: Calculus, Algorithm, and Completeness
NIPS 2022
Unravelling the Performance of Physics-informed Graph Neural Networks for Dynamical Systems
NIPS 2022
MissDAG: Causal Discovery in the Presence of Missing Data with Continuous Additive Noise Models
NIPS 2022
A Theoretical Study on Solving Continual Learning
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
Falsification before Extrapolation in Causal Effect Estimation
NIPS 2022
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