Counterfactual Inference

12 papers with code • 0 benchmarks • 1 datasets

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Greatest papers with code

Deep Kalman Filters

clinicalml/structuredinference 16 Nov 2015

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

Deep Structural Causal Models for Tractable Counterfactual Inference

biomedia-mira/deepscm NeurIPS 2020

We formulate a general framework for building structural causal models (SCMs) with deep learning components.

Counterfactual Inference Normalising Flows +1

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

d909b/perfect_match ICLR 2019

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

Counterfactual VQA: A Cause-Effect Look at Language Bias

yuleiniu/cfvqa 8 Jun 2020

VQA models may tend to rely on language bias as a shortcut and thus fail to sufficiently learn the multi-modal knowledge from both vision and language.

Counterfactual Inference Question Answering +1

Learning Representations for Counterfactual Inference

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

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 +1

Counterfactual diagnosis

babylonhealth/counterfactual-diagnosis 15 Oct 2019

We show that this approach is closer to the diagnostic reasoning of clinicians and significantly improves the accuracy and safety of the resulting diagnoses.

Counterfactual Inference Decision Making +1

MultiVerse: Causal Reasoning using Importance Sampling in Probabilistic Programming

babylonhealth/multiverse 17 Oct 2019

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

Counterfactual Inference Probabilistic Programming

A Structural Causal Model for MR Images of Multiple Sclerosis

jcreinhold/counterfactualms 4 Mar 2021

Precision medicine involves answering counterfactual questions such as "Would this patient respond better to treatment A or treatment B?"

Counterfactual Inference Disease Prediction

Leveraging Structured Biological Knowledge for Counterfactual Inference: a Case Study of Viral Pathogenesis

bel2scm/bel2scm 13 Jan 2021

This manuscript proposes a general approach for querying a causal biological knowledge graph, and converting the qualitative result into a quantitative structural causal model that can learn from data to answer the question.

Counterfactual Inference

RNN-based counterfactual prediction, with an application to homestead policy and public schooling

jvpoulos/rnns-causal 10 Dec 2017

This paper proposes a method for estimating the effect of a policy intervention on an outcome over time.

Counterfactual Inference Time Series +1