I have been reading Pearl's book to understand how Bayesian networks and causal discovery might work. Other than Pearl, I haven't yet found a rigorous, systematic approach to causal inference from observational data. The theorems and algorithms he presents (e.g. Inductive Causation) look convincing to me, however, it appears that causal discovery is very much in research. I was wondering if anyone had any experience applying any of this research or knows of any other, strongly supported methods of causal inference.
2026-04-01 15:40:55.1775058055
Research and application of causal inference
191 Views Asked by Bumbble Comm https://math.techqa.club/user/bumbble-comm/detail At
1
There are 1 best solutions below
Related Questions in CONDITIONAL-PROBABILITY
- Given $X$ Poisson, and $f_{Y}(y\mid X = x)$, find $\mathbb{E}[X\mid Y]$
- Finding the conditional probability given the joint probability density function
- Easy conditional probability problem
- Conditional probability where the conditioning variable is continuous
- probability that the machine has its 3rd malfunction on the 5th day, given that the machine has not had three malfunctions in the first three days.
- Sum of conditional probabilities equals 1?
- Prove or disprove: If $X | U$ is independent of $Y | V$, then $E[XY|U,V] = E[X|U] \cdot E[Y|V]$.
- Conditional probability and binomial distribution
- Intuition behind conditional probabilty: $P(A|B)=P(B\cap A)/P(B)$
- Transition Probabilities in Discrete Time Markov Chain
Related Questions in BAYESIAN
- Obtain the conditional distributions from the full posterior distribution
- What it the posterior distribution $\mu| \sigma^2,x $
- Posterior: normal likelihood, uniform prior?
- If there are two siblings and you meet one of them and he is male, what is the probability that the other sibling is also male?
- Aggregating information and bayesian information
- Bayesian updating - likelihood
- Is my derivation for the maximum likelihood estimation for naive bayes correct?
- I don't understand where does the $\frac{k-1}{k}$ factor come from, in the probability mass function derived by Bayesian approach.
- How to interpret this bayesian inference formula
- How to prove inadmissibility of a decision rule?
Trending Questions
- Induction on the number of equations
- How to convince a math teacher of this simple and obvious fact?
- Find $E[XY|Y+Z=1 ]$
- Refuting the Anti-Cantor Cranks
- What are imaginary numbers?
- Determine the adjoint of $\tilde Q(x)$ for $\tilde Q(x)u:=(Qu)(x)$ where $Q:U→L^2(Ω,ℝ^d$ is a Hilbert-Schmidt operator and $U$ is a Hilbert space
- Why does this innovative method of subtraction from a third grader always work?
- How do we know that the number $1$ is not equal to the number $-1$?
- What are the Implications of having VΩ as a model for a theory?
- Defining a Galois Field based on primitive element versus polynomial?
- Can't find the relationship between two columns of numbers. Please Help
- Is computer science a branch of mathematics?
- Is there a bijection of $\mathbb{R}^n$ with itself such that the forward map is connected but the inverse is not?
- Identification of a quadrilateral as a trapezoid, rectangle, or square
- Generator of inertia group in function field extension
Popular # Hahtags
second-order-logic
numerical-methods
puzzle
logic
probability
number-theory
winding-number
real-analysis
integration
calculus
complex-analysis
sequences-and-series
proof-writing
set-theory
functions
homotopy-theory
elementary-number-theory
ordinary-differential-equations
circles
derivatives
game-theory
definite-integrals
elementary-set-theory
limits
multivariable-calculus
geometry
algebraic-number-theory
proof-verification
partial-derivative
algebra-precalculus
Popular Questions
- What is the integral of 1/x?
- How many squares actually ARE in this picture? Is this a trick question with no right answer?
- Is a matrix multiplied with its transpose something special?
- What is the difference between independent and mutually exclusive events?
- Visually stunning math concepts which are easy to explain
- taylor series of $\ln(1+x)$?
- How to tell if a set of vectors spans a space?
- Calculus question taking derivative to find horizontal tangent line
- How to determine if a function is one-to-one?
- Determine if vectors are linearly independent
- What does it mean to have a determinant equal to zero?
- Is this Batman equation for real?
- How to find perpendicular vector to another vector?
- How to find mean and median from histogram
- How many sides does a circle have?
Causal inference, in the form of many algorithms that evolved from ideas Pearl (et. al.) presented in the papers the book you mention is based on are abundant, sometimes with marked success. This book will give plenty of algorithms and applications.
One striking application is the construction of a Bayesian network for the diagnosis of complicated lung conditions. The network performs almost as well as a team of expert lung doctors. There are many others for, e.g., robots traveling through a maze, computer vision, OCRs etc.