causal inference

Feb 24 2024

Inducing time-asymmetry on reversible classical statistical mechanics via Interventional Thermodynamic Ensembles (ITEs).

msuzen

Preamble Probably, one of the most fundamental issue in classical statistical mechanics is extending reversible dynamics to many-particle systems that behaves irreversibly. In other words, how time's arrow appears even though constituted systems evolves in reversible dynamics. This is the main...

thermodynamics causality statistical physics dynamical systems statistical ensemble causal inference

Nov 25 2023

Why should there be no simultaneity rule for causal models?

msuzen

Dominos in motion (Wikipedia)Preamble The definition of weighted directed graphs (wDAGs) provides a great opportunity to express causal relationships among given variates. Usually this is expressed as SCMs, Structural Causal Model or in more generally causal model. A given causal model can be...

causality dags time-series scm graph theory causal inference

Nov 10 2023

Mathematical Definition of Heuristic Causal Inference: What differentiates DAGs and do-calculus?

msuzen

Preamble David Hume (Wikipedia)Experimental design is not a new concept and randomised control trials (RCTs) are our solid gold standard of doing quantitative research, when no apparent physical laws are available to validate observations.  However, it is very expensive to design RCTs, not ethical...

causality applied mathematics dags graph theory causal inference randomness heuristic intervention random control trials counterfactual bayesian inference

Sep 09 2023

Practical causal ordering: Why weighted-Directed Acyclic Graphs (DAGs) are powerful for causal inference?

msuzen

Preamble Fractal Tree (Wikipedia)A quiet causal inference revolution is underway in industry. We see immense success of transformers deep learning architectures. However their success should also be attributed to causal modelling. Large Language Models (LLMs), specially closed-sourced ones,...

llm nlp causality dag self-attention dags wdags large language models causal inference

Dec 29 2020

Practice causal inference: Conventional supervised learning can't do inference

msuzen

Domino OR-gate (Wikipedia)PreambleA trained model may provide predictions about input values it may never seen before but it isn't an inference, at least for 'classical' supervised learning. In reality it provides an interpolation from the training-set, i.e., via function...

machine learning causality supervised learning inference causal inference

Jan 11 2019

The fundamental problem of causal inference: causality resource list Looper

msuzen

Preamble One of the main tenants of practical data science is performing statistical inference on data sets which are assumed to be representations of populations of activity, natural or man-made. A specific case is called causal inference, which probably the core interest of decision makers...

machine learning causality rubin causal model randomised control trial matching do calculus uplift modelling bayesian networks statistics causal inference pearl a-null test imputation