Indro Spinelli

Hi, this is one of the downsides of our method and the codebase is starting to show its age. You could try to build the graph starting from a KNN...

Hi, Like you, I was trying to replicate the results in the paper. For syn1 and syn2 evaluating the set of nodes in range(400,700,5) almost matches the AUCs provided. For...

That version of CORA-ML was introduced here https://arxiv.org/abs/1707.03815. It was later used also here https://arxiv.org/abs/1810.05997 which is the paper that we use for our comparisons. On Fri, Apr 10, 2020...

Hi! If you use degrade_dataset it is supposed that the raw data is perfect and you want to create missing values. By the way, if your raw data has already...

Hi, You are probably using a newer version of DGL. In fact, the function you are calling is deprecated. Try using an older version. Alternatively, you can find the newer...

Hi, GINN is not built for this purpose, however new approaches handle the imputation for temporal data

Hi! MAE and RMSE can be computed on artificially induced missing values of course. The function imputation_accuracy takes 3 arguments, the original dataset, the imputed one and the mask indicating...

Hi, GINN is part of a family of algorithms whose objective is the imputation of missing values. Basically, you have a dataset which is incomplete (i.e. some of the observations...

Not exactly. The task here is to learn from the incomplete data the values that most likely should fill the gaps in the dataset. After this imputation step, you have...