Causal Inference
3개 벤치마크 · 논문 2,147편 · 이 태스크의 논문 보기 →
Benchmarks
Most implemented
Unbiased Scene Graph Generation from Biased Training
Causal Effect Inference with Deep Latent-Variable Models
DoWhy: An End-to-End Library for Causal Inference
Adapting Neural Networks for the Estimation of Treatment Effects
Adapting Text Embeddings for Causal Inference
Double/Debiased Machine Learning for Treatment and Causal Parameters
Papers
Causal Foundation Models
Causal inference is the practice of estimating the effect of a treatment or intervention from data. It traditionally requires a bespoke pipeline for every new problem: first proposing a causal mechanism, selecting a comp…
Causal InferenceLearning to Allocate Incentives for Incentivized Advertising via Offline Model-Based Reinforcement Learning
Complete your ad view and grab a 5-cent bonus! In incentivized advertising, a platform promises users a bonus before observing downstream ad revenue, encouraging them to click and complete ads. It must balance the incent…
Reinforcement LearningCausal InferenceOffline RL4DStreamCtrl: Interactive Video Generation with Online 4D Control
Generative video models now synthesize footage nearly indistinguishable from reality. Their promise as interactive tools hinges on fine-grained control of how objects and the camera move over time, yet each existing appr…
Video GenerationCausal InferenceLet Time Tell: Identification and Gaussian Process Estimation for Interrupted Time Series
We study causal inference in interrupted time series designs where a treatment affects every unit simultaneously, so that the contemporaneous controls used by difference-in-differences and synthetic control are unavailab…
Causal InferenceA Causal Inference Approach for Evaluating Diagnostic Tests and AI-Enabled Medical Devices: From Effect Modification to Information-Augmented Decision-Making
Diagnostic medical tests and devices provide useful information for evaluating the potential benefits and risks of therapeutic treatments. However, unlike treatments, their impact on health outcomes is generally indirect…
Causal InferenceDoubly Robust Estimation of Causal Effect on CVR with Targeted Regularization
Post-click conversion rate (CVR) is a key metric in various scenarios including e-commerce and advertising, reflecting the efficiency and user experience in the second stage of the conversion process. Estimating the caus…
Causal Inference