Research map / Learning theory and algorithms / Sample complexity
On the Representation Power of Set Pooling Networks
Read the paperCheck your idea against 108,967 papers
AI-extracted summary. Written by AI from the paper's title only (no summary yet). Numbers and claims can be wrong or missing context, so check the paper before you cite or build on it.
Closest papers by meaning
- PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space (NeurIPS 2017 · similarity 0.86)
- Polynomial Width is Sufficient for Set Representation with High-dimensional Features (ICLR 2024 · similarity 0.86)
- Disentangling Trainability and Generalization in Deep Neural Networks (ICML 2020 · similarity 0.86)
- On Infinite-Width Hypernetworks (NeurIPS 2020 · similarity 0.86)
- Improving Set Function Approximation with Quasi-Arithmetic Neural Networks (ICLR 2026 · similarity 0.86)
- A Universal Approximation Theorem of Deep Neural Networks for Expressing Probability Distributions (NeurIPS 2020 · similarity 0.85)
Writing a paper in this area? scime draft is a free LaTeX editor with AI included, real-time co-authors and a check of your references and venue rules before you submit. It also imports OpenAI Prism projects.