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Counterfactual Inference

6 papers with code · Miscellaneous
Subtask of Causal Inference

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Deep Kalman Filters

16 Nov 2015clinicalml/structuredinference

Motivated by recent variational methods for learning deep generative models, we introduce a unified algorithm to efficiently learn a broad spectrum of Kalman filters.

COUNTERFACTUAL INFERENCE TIME SERIES

Perfect Match: A Simple Method for Learning Representations For Counterfactual Inference With Neural Networks

ICLR 2019 d909b/perfect_match

However, current methods for training neural networks for counterfactual inference on observational data are either overly complex, limited to settings with only two available treatments, or both.

COUNTERFACTUAL INFERENCE

Learning Representations for Counterfactual Inference

12 May 2016lightlightdyy/Deep-Learning-and-Causal-Inference

Observational studies are rising in importance due to the widespread accumulation of data in fields such as healthcare, education, employment and ecology.

COUNTERFACTUAL INFERENCE DOMAIN ADAPTATION REPRESENTATION LEARNING

MultiVerse: Causal Reasoning using Importance Sampling in Probabilistic Programming

17 Oct 2019babylonhealth/multiverse

We elaborate on using importance sampling for causal reasoning, in particular for counterfactual inference.

COUNTERFACTUAL INFERENCE PROBABILISTIC PROGRAMMING

RNN-based counterfactual prediction

10 Dec 2017jvpoulos/rnns-causal

This paper proposes an alternative to the synthetic control method (SCM) for estimating the effect of a policy intervention on an outcome over time.

COUNTERFACTUAL INFERENCE TIME SERIES TIME SERIES PREDICTION