5 problems

Identifiability conjecture for causal models with $H_1$ entropy
Consider the causal model $\mathcal{M}=(\{X,Y\},E,f,X\rightarrow Y,p_{X,E})$ , where the discrete random variables $X$ and $Y$ have $n$ states, $E$ is independent of $X$ and has…
opencausal-inference entropy identifiability
0 responses
05
Separated presentation adjunction for causal and triangular Frobenius presentations
Let $\mathbf{Caus}$ be the category of finite acyclic directed graphs equipped with a chosen topological order, with order-preserving graph homomorphisms or refinements as morphism…
opencategory-theory causal-inference frobenius-algebras
0 responses
07
Non-vacuity of improved covariate-adjusted variance
Let $\nu^{\mathsf{rd}}$ , $\nu^{\mathsf{rd}\dag}$ , and $\mathsf{var}(\widehat{\tau}_{\mathsf{unadj}})$ denote the variance quantities defined in the paper for the covariate-adjusted…
opencausal-inference covariate-adjustment randomized-experiments
0 responses
05
Strict inclusion conjecture for causal information integration and causal information structure
Let $\mathcal{M}_{CII}$ denote the model of causal information integration and let $\mathcal{M}_{CIS}$ denote the model of causal information structure, with…
opencausal-inference information-theory probabilistic-models
0 responses
06
The strict causal penalty conjecture for optimal teaching and learning
Causal penalty conjecture. The optimal learning rate of the student is strictly less than
opencausal-inference information-theory learning-theory
0 responses
04

5 problems

Identifiability conjecture for causal models with H1H_1H1​ entropy

Separated presentation adjunction for causal and triangular Frobenius presentations

Non-vacuity of improved covariate-adjusted variance

Strict inclusion conjecture for causal information integration and causal information structure

The strict causal penalty conjecture for optimal teaching and learning

Identifiability conjecture for causal models with $H_1$ entropy