Chen-Cai-OSU

I am looking for ``` model = topk(**kw)/random(*kw) model.recommend_k_items ```

I think that's too much work for a new user to just establish the baseline, which is in sharp contrast to other models that is much more sophisticated but is...

Hi, I am also interested in understandiny why matrix factorization performs poorly on Movielens data in terms of precison@k and recall@k. https://github.com/microsoft/recommenders/blob/main/examples/06_benchmarks/movielens.ipynb here listed some benchmark dataset where another MF...

Hi, Thanks for implementing RotatE. I ran the doctest but get a different result: model = RotatE(batches_count=1, seed=555, epochs=20, k=10, loss = 'pairwise', loss_params = {'margin': 1}, regularizer = 'LP',...

I compare your implementation with the original implementation. It seems that in the original implementation, there is mode called head-batch, and your implementation correspond to the original implementation when the...

Thank you very much for the clarification. I will be waiting for the RotatE to be fully implemented.

Thanks for the update! May I know how large is the gap between the current performance and the reported performance in the paper?

Hello, Is the implementation of RotatE still ongoing?

I think if users are allowed to manipulate the filtrations, I can just change the filtration value for each simplex without changing the order of the filtration. However, this doesn't...

Thank you for the explanation. What I don't understand is that when I run the following code, ``` model = GCN(10, 10, 10, 10, 2, device='cpu').to('cuda:3') print(model) ``` I got...