
## Mappings for Marginal Probabilities with Applications to Models in Statistical Physics
Mehdi Molkaraie
Keywords: 
JMLR/2022/Proceedings/210200 - Mappings for Marginal Probabilities with Applications to Models in Statistical Physics.pdf
Project URL: nan

### Implementation
_Given the documentation given by the authors on the method, how much time investment would it be to re-implement the method from scratch?_

[9]

The authors refer for an algorithm they use in sec 8 to a library. Other than that the authors do not share details on their implementation.

### Data
_Given the data description in the documentation, how much effort take to either: Find the same dataset the authors used, or similar datasets and defend the comparability, or acquire one from scratch?_

[5]

(1/1)

The authors conduct experiments on simulated data and describe them in section 8/9 with details and parameter values per experiment. Part of the simulator code is referred to a library (citation). Other than that the implementation is not shared of the simulators.

### Configuration 
_Given the (hyper)parameters, including semantic parameters, of the method: How much effort would it take to acquire the algorithm configurations used for their results, and compare against their budgetary constraints?_

[5]

The authors state the parameter values in 9.1 but no overview and or acquisition given.

### Experimental Procedure
_Given the experimental set-up of the work, how difficult is it to set up a new experiment, similar to those presented in the original work, with the same procedure?_

[1]

The authors measure relative error and estimated marginal variances (formulae give) over single runs averaged over the number of samples. No data split. 

### Expertise
_How much effort would it take to acquire the expertise required to reproduce the work independently relying on the available documentation?_

[10]

Requires expertise on ising model, statistical physics and marginal probabilities.
