You are provided with a research question, keyphrases about the question, a description of candidate datasets and dataset options. Read the description of popular datasets provided below and select the ones that can be used to validate the following research question. Use your knowledge of machine learning datasets to make the best judgement.
Your response should be formatted as a `json` array. For instance, for the query "Semi supervised image classification", a sample response might be: ["CIFAR-10", "CIFAR-100"]. Do not include any extra text in the response other than the answer array.

Query: The goal of network representation learning is to encode the network structure information into a continuous low-

Keyphrases: network representation learning

Dataset description:
DBLP: The DBLP is a citation network dataset. The citation data is extracted from DBLP, ACM, MAG (Microsoft Academic Graph), and other sources.
Make3D: The Make3D dataset is a monocular Depth Estimation dataset that contains 400 single training RGB and depth map pairs, and 134 test samples. The RGB images have high resolution, while the depth maps are provided at low resolution.
MUTAG: In particular, MUTAG is a collection of nitroaromatic compounds and the goal is to predict their mutagenicity on Salmonella typhimurium. Input graphs are used to represent chemical compounds, where vertices stand for atoms and are labeled by the atom type (represented by one-hot encoding), while edges between vertices represent bonds between the corresponding atoms.
Cora: The Cora dataset consists of 2708 scientific publications classified into one of seven classes. The citation network consists of 5429 links.
Pubmed: The Pubmed dataset consists of 19717 scientific publications from PubMed database pertaining to diabetes classified into one of three classes. The citation network consists of 44338 links.

Options:- A: DBLP  B: Make3D  C: MUTAG  D: Cora  E: Pubmed
["DBLP", "Cora", "Pubmed"]