## Effective Structural Encodings via Local Curvature Profiles
Lukas Fesser, Melanie Weber
Keywords: 
ICLR/2024/Proceedings/19035 - Effective Structural Encodings via Local Curvature Profiles.pdf
Project URL: nan

### Implementation
_Given the documentation shared by the authors on a new method, how much effort would it be to re-implement the method from scratch?_

[2]

Authors provide a link to the implementation in footnote 1 of the abstract (https://github.com/Weber-GeoML/Local_Curvature_Profile). Readme has installation instructions, how to run the code for various experiments. Code has few comments.

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

[3]

(6/6)

Enzymes, Imdb, Mutag, and Proteins, Cora and Citeseer. No details. Downloads automatically in code.

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

[2]

HP values and architectures detailed in text in appendix A.2. and A.3. including search. Structured overview missing.

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

[1]

Authors repeat experiments for 100 trials, report mean test accuracy and 95% CI. Data split given in appendix A.3.

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

[2]

-
