
## Modeling Random Networks with Heterogeneous Reciprocity
Daniel Cirkovic, Tiandong Wang
Keywords: 
JMLR/2024/Proceedings/221317 - Modeling Random Networks with Heterogeneous Reciprocity.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?_

[10]

Implementation not given.

### 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?_

[2]

(2/2)

The authors conduct experiments on simulated data as well as datasets. The simulation is described with parameters in section 5. Simulator implementation not given. Datasets are Facebook wallposts and Reddit comment data. The datasets are described in 6.1. and 6.2. citations are given and staistics as well. No direct links.

### 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?_

[8]

The authors state the parameters of the method in algorithm 1, 2, 3 and 4. Their values are defined in section 4, 5 and 6 but for a large part this is unclear.

### 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 report average +std error for 100 networks in table 1 as well as coverage percentage. Data split not applicable (no training). 

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

[8]

Requires expertise on variationa linference and bayesian methods.
