Comments (2)
Hello Da,
I put here my reply to Xiang Song in the other thread I opened at the github page of DGL.
Hi Xiang,
That is great! Myself (PhD Researcher) and a group of Master students from TU Berlin, we work on extending/implementing properly a set of Graph Embedding (GE) algorithms atop DGL(-KE) system.
We believe your system has great potential and this is why we chose it.
Sure, we want to contribute so that our implementation and efforts become part of DGL. This would be awesome. One of us is working on DeepWalk, so maybe we can be
And LINE is also into our scheme of things and we plan to implement it. So, yes we want to implement this.
Can I put my team in the loop?
Best,
Makis
We are willing to contribute to DGL(-KE), so let us know how we get in the loop.
Now, we started working on DeepWalk, node2vec (random walk-based) and VERSE (PPR-based) algorithms.
Best,
Makis
from dgl-ke.
Hello Makis,
DGL-KE was developed for KGE models, so we didn't have an interface that natively fit for models such as DeepWalk. However, I believe with some modification, DGL-KE can support DeepWalk as well. In fact, we are developing such a model in DGL and we plan to move it to DGL-KE when it's ready for large graphs. In the process, we'll explore how to generalize the current DGL-KE implementation for models such as DeepWalk. So to answer your question, yes, it's possible to build such abstractions.
Best,
Da
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Related Issues (20)
- Upgrade DGL dependency HOT 2
- Can DGL_KE models be implemented on dynamic knowledge graphs? HOT 1
- Force dtype to int64 to ensure that we don't index with non-long tensor
- IndexError: list index out of range when training on raw user defined knowledge graph HOT 4
- Support Adam or Adagrad HOT 8
- Can not install dgl 0.4.3 HOT 4
- DGLBACKEND s not recognized as an internal or external command HOT 1
- No module named 'ogb
- whether just assign vertexes but not the edges together with on graph partition when use METIS
- [BUG] Quick start example code does not work HOT 4
- dgl.__version__ >= 0.8 breaks on partition.py HOT 2
- RuntimeError: Cannot re-initialize CUDA in forked subprocess HOT 1
- Multi-gpu training is not effective on specific cases
- `graph.HeteroGraph` Error happened when running example HOT 1
- !DGLBACKEND=pytorch dglke_train Not Working HOT 1
- pytorch dglke_train Not Working, Expected type graph.Graph but get graph.HeteroGraph HOT 3
- can't train my KG ,it keeps telling me 'AssertionError: test set is not provided' HOT 1
- Installation error, no corresponding version HOT 1
- DGL-KE TransR Predict Error
- 'dgl' has no attribute '_deprecate'
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