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Causal Inference for Heterogeneous Data and Information Theory

The present reprint, “Causal Inference for Heterogeneous Data and Information Theory”, is a special issue of Journal Entropy. This Special Issue belongs to the section "Information Theory, Probability, and Statistics". The reprint gathers thirteen original contributions of leading experts in the the...

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Enregistré dans:
Format: Online
Langue:anglais
Publié: MDPI - Multidisciplinary Digital Publishing Institute 2023
Sujets:
common hidden cause
graphical models
probabilistic models
Chain Event Graphs
interventions
causal calculus
causal fairness
responsible data science
causal discovery
Hawkes process
high-dimensional statistics
hidden confounder
causality
Bitcoin
inflation
yield spreads
approximation theory
Hellinger distance
Kullback–Leibler divergence
correct specification
misspecified models
causal inference
instrumental variables
neural networks
doubly robust estimation
semi-parametric theory
instrumental variable
causal graph
non-Gaussianity
causal graphs
dynamic systems
causal learning
time
continuous
event cognition
econometrics software
causal machine learning
statistical learning
conditional average treatment effects
individualized treatment effects
multiple treatments
selection-on-observables
piecewise linear
thresholds model
causal Inference
regularization
BART
Stan
machine learning
heterogeneous treatment effects
multilevel data
grouped data
artificial intelligence
higher-order category theory
statistics
n/a
thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries
thema EDItEUR::U Computing and Information Technology::UY Computer science
Accès en ligne:ONIX_20230808_9783036580500_27
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