geometric structures
Geometric structures in AI refer to the properties and arrangements of data in multi-dimensional spaces. Understanding these structures can provide insights into relationships and clustering for various machine learning tasks.
- An Efficient Orlicz-Sobolev Approach for Transporting Unbalanced Measures on a Graph
- Dataset Distillation of 3D Point Clouds via Distribution Matching
- SegGraph: Leveraging Graphs of SAM Segments for Few-Shot 3D Part Segmentation
- Sharper Convergence Rates for Nonconvex Optimisation via Reduction Mappings
- Spiral: Semantic-Aware Progressive LiDAR Scene Generation and Understanding