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Causality/paper

• [IGC-Net] CAPO Estimation over Time

  Causality/paper 2026. 3. 30. 22:43

  K.Hess 님 논문을 보고있자면, '이런 분들이 연구자구나..!' 싶다.정말 연구 찰지게 잘하시는 것 같다. 그간 논문을 쭉 읽어왔는데, K.Hess님은 longitudinal causal effect estimation 분야에서, continuous regime, IPW를 이용한 adjustment, bayesian inference를 모두 publish했고, transformer based g-computation을 구현하고, 여기에서 파생되는 high variance 문제를 addressing하기 위한 regression based approach를 본 논문에서 또한 새롭게 다루신다. 나는 pseudo outcome을 이용한 g-computation 기법에 집중하느라 논문의 모든 내용을 가져오진 ..

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• [GT] G-Transformer: Counterfactual Outcome Prediction under Dynamic and Time-varying Treatment Regimes

  Causality/paper 2026. 3. 1. 13:51

  CVSim & MIMIC-IV Results 생략....

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• [SCIP-Net] Stabilized Neural Prediction of Potential Outcomes in Continuous Time

  Causality/paper 2026. 2. 19. 22:37

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• [G-Net] a Recurrent Network Approach to G-Computation for Counterfactual Prediction Under a Dynamic Treatment Regime

  Causality/paper 2026. 2. 19. 13:35

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• [RMSNs] Forecasting Treatment Responses Over Time Using Recurrent Marginal Structural Networks

  Causality/paper 2026. 2. 19. 10:29

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• [CT] Causal Transformer for Estimating Counterfactual Outcomes

  Causality/paper 2026. 2. 19. 08:21

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• [CRN] Estimating Counterfactual Treatment Outcomes over Time through Adversarially Balanced Representations

  Causality/paper 2026. 2. 18. 18:26

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• [BNCDE] Bayesian Neural CDEs for Treatment Effect Estimation

  Causality/paper 2026. 1. 19. 22:18

  https://arxiv.org/pdf/2310.17463https://github.com/konstantinhess/Bayesian-Neural-CDE GitHub - konstantinhess/Bayesian-Neural-CDEContribute to konstantinhess/Bayesian-Neural-CDE development by creating an account on GitHub.github.com(ICLR 2024)To be continued.. See you soon!

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