
## Spatio-Temporal Pivotal Graph Neural Networks for Traffic Flow Forecasting
Weiyang Kong, Ziyu Guo, Yubao Liu
Keywords: DMKM: Mining of Spatial, Temporal or Spatio-Temporal Data
AAAI/2024/Proceedings/29368 - Spatio-Temporal Pivotal Graph Neural Networks for Traffic Flow Forecasting.pdf

### 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]

The authors provide no source material of their implementation in their work. The authors do provide detailed illustrations on their framework, but no pseudo code, details on their implementation such as programming language or libraries used can be found.

### 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?_

[1]

(7/7)

The authors use seven public datasets and cite their sources. A description on each data set is given.

### 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?_

[10]

The authors note that they sate a hyperparameter K emperically to a formula and analyse the impact of this parameter. No other hyperparameters are reported.

### 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 describe how the data is divided for tresting purposes and which metrics will be used. They also sate that each experiment is repeated five times and that averages are reported.

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

[8]

The paper is from the domain of geometric deep learning, and the independent investigators would need to have previous experience in order to reproduce the paper. On top of this, the paper deals with spatio-temporal data, which also requires previous experience. The lack of documentation on the execution of the presented method substantially increases this, as the independent investigators would need to do extenstive research to fill the missing gaps.
