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Counterfactual Inference

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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/tridungduong16/counterfactual_fairness_game_theoretic

공식 코드

Achieving Counterfactual Fairness with Imperfect Structural Causal Model

https://github.com/valentyn1997/csm-apid

공식 코드

Partial Counterfactual Identification of Continuous Outcomes with a Curvature Sensitivity Model

https://github.com/weitianxin/MACR

공식 코드

Model-Agnostic Counterfactual Reasoning for Eliminating Popularity Bias in Recommender System

https://github.com/weiyinwei/kgcr

공식 코드

Causal Inference for Knowledge Graph based Recommendation

https://github.com/wenjiewwj/ucrs

공식 코드

User-controllable Recommendation Against Filter Bubbles

https://github.com/wzsong17/coco-sbrs

공식 코드

A Counterfactual Collaborative Session-based Recommender System

https://github.com/xinshuli2022/sdd

공식 코드

Self-Distilled Disentangled Learning for Counterfactual Prediction

https://github.com/xuesong39/dac

공식 코드

Doubly Abductive Counterfactual Inference for Text-based Image Editing

https://github.com/yaochenzhu/psf-vae

공식 코드

Path-Specific Counterfactual Fairness for Recommender Systems

https://github.com/yuleiniu/cfvqa

공식 코드

Counterfactual VQA: A Cause-Effect Look at Language Bias

https://github.com/zenzendatabase/personpersuasion

공식 코드

Generative Framework for Personalized Persuasion: Inferring Causal, Counterfactual, and Latent Knowledge

https://github.com/zexusun/oilca-neurips23

공식 코드

Offline Imitation Learning with Variational Counterfactual Reasoning

https://github.com/zhang-xiaokun/dimo

공식 코드

Disentangling ID and Modality Effects for Session-based Recommendation

https://github.com/GalaxyFox/DS-GA-3001-Deep_Kalman_Filter

Deep Kalman Filters

https://github.com/aashish-khub/NearestNeighbors

Counterfactual inference for sequential experiments

https://github.com/abraich/pycaus

SurvCaus : Representation Balancing for Survival Causal Inference

https://github.com/anpwu/der-cfr

Learning Decomposed Representation for Counterfactual Inference

https://github.com/babylonhealth/multiverse

MultiVerse: Causal Reasoning using Importance Sampling in Probabilistic Programming

https://github.com/biomedia-mira/causal-gen

Deep Structural Causal Models for Tractable Counterfactual Inference

https://github.com/clinicalml/dmm

Deep Kalman Filters

https://github.com/jameszhou-gl/cbre

Cycle-Balanced Representation Learning For Counterfactual Inference

https://github.com/lenyabloko/SemEval2020

SemEval-2020 Task 5: Counterfactual Recognition

https://github.com/paidamoyo/counterfactual_survival_analysis

Enabling Counterfactual Survival Analysis with Balanced Representations

https://github.com/sschrod/adbcr

Learning Representations for Counterfactual Inference

https://github.com/tatsu432/BDCM

Modeling Causal Mechanisms with Diffusion Models for Interventional and Counterfactual Queries

https://github.com/tychen-SJTU/MECD-Benchmark

MECD+: Unlocking Event-Level Causal Graph Discovery for Video Reasoning

https://github.com/valentyn1997/au-cnfs

Counterfactual Mean Embeddings

https://github.com/wenjiewwj/clickbait

Clicks can be Cheating: Counterfactual Recommendation for Mitigating Clickbait Issue

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