- Tutorial on Graph Neural Networks for Computer Vision and Beyond with PyTorch examples (Part 2 will be coming soon) https://medium.com/@BorisAKnyazev/tutorial-on-graph-neural-networks-for-computer-vision-and-beyond-part-1-3d9fada3b80d 3 comments learnmachinelearning
Linked pages
- Adjacency matrix - Wikipedia https://en.wikipedia.org/wiki/Adjacency_matrix 54 comments
- HyperFoods: Machine intelligent mapping of cancer-beating molecules in foods | Scientific Reports https://www.nature.com/articles/s41598-019-45349-y 38 comments
- [1611.03530] Understanding deep learning requires rethinking generalization https://arxiv.org/abs/1611.03530 24 comments
- Graph (abstract data type) - Wikipedia http://en.wikipedia.org/wiki/Graph_(abstract_data_type) 12 comments
- Set (abstract data type) - Wikipedia https://en.wikipedia.org/wiki/Set_(abstract_data_type) 8 comments
- [1603.07285] A guide to convolution arithmetic for deep learning https://arxiv.org/abs/1603.07285 0 comments
- Graph Neural Network and Some of GNN Applications: Everything You Need to Know - neptune.ai https://neptune.ai/blog/graph-neural-network-and-some-of-gnn-applications 0 comments
- [1905.10498] Cold Case: The Lost MNIST Digits https://arxiv.org/abs/1905.10498 0 comments
- How Can Neural Network Similarity Help Us Understand Training and Generalization? – Google AI Blog https://ai.googleblog.com/2018/06/how-can-neural-network-similarity-help.html 0 comments
- CelebA Dataset http://mmlab.ie.cuhk.edu.hk/projects/CelebA.html 0 comments
- NetworkX — NetworkX documentation https://networkx.github.io/ 0 comments
- neptune.ai | The MLOps stack component for experiment tracking https://neptune.ai 0 comments
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