Causal Inference

Causality Models, Reasoning and Inference: Causal Data Science Course

DSA ADS Course - 2021

Causal Analysis, Causality Models, Causal Inference

Discuss causal analysis and how it applies to many different fields like health policy and medical practice, public policy, business decisions, statistics, artificial intelligence, economics, philosophy, cognitive science, and others. Review probabilistic, manipulative, counterfactual, and structural approaches to causation and apply simple mathematical tools for studying the relationships between causal connections and statistical associations.

CausaLM: Causal Model Explanation Through Counterfactual Language Models

DSA ADS Course - 2021

Causal Data Science, Causal Inference, Linguistic Causation, CausaLM, Causal Model Explanation, Counterfactual Language Models, Machine Learning

Discuss causative linguistic expressions and causal model explanation through counterfactual language models.

CausaLM: Causal Model Explanation Through Counterfactual Language Models - 2021

Abstract

Modelling Linguistic Causation

DSA ADS Course - 2021

Causal Data Science, Causal Inference, Linguistic Causation, Structural Equation Modelling

Discuss causative linguistic expressions, how causal relations are expressed in natural languages, and Structural Equation Modelling (SEM).

Modelling Linguistic Causation - 2021

Abstract

DoWhy: Addressing Challenges in Expressing and Validating Causal Assumptions

DSA ADS Course - 2021

DoWhy, Causal Assumptions, Causal Inference, Causal Data Science, Machine Learning

Discuss successful application of causal inference techniques.  As computing systems are more frequently and more actively intervening in societally critical domains such as healthcare, education, and governance, it is critical to correctly predict and understand the causal effects of these interventions. Without an A/B test, conventional machine learning methods, built on pattern recognition and correlational analyses, are insufficient for decision-making.

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