Completed
- Intro & Overview
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Classroom Contents
Is Distance Matrix Enough for Geometric Deep Learning?
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- 1 - Intro & Overview
- 2 - Incompleteness of Vanilla DisGNN
- 3 - k-DisGNNs
- 4 - Extracting High-Order Geometric Information
- 5 - Unifying Invariant Geometric Models
- 6 - Completeness and Universality
- 7 - Experiments
- 8 - Experiments: MD17
- 9 - Experiments: rMD17
- 10 - Experiments: QM9 and Effectiveness of Edge Repr
- 11 - Discussion
- 12 - Q+A
