Notice: The reproducibility variables underlying each score are classified using an automated LLM-based pipeline, validated against a manually labeled dataset. LLM-based classification introduces uncertainty and potential bias; scores should be interpreted as estimates. Full accuracy metrics and methodology are described in Coakley et alK. L. Coakley, T. Snelleman, H. Hoos, and O. E. Gundersen, "The embrace of open science: An analysis of a decade of AI research and 56 800 conference papers," Under Review, 2026..
On the Universality of Invariant Networks
Authors: Haggai Maron, Ethan Fetaya, Nimrod Segol, Yaron Lipman
ICML 2019 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | We present two main results: First, G-invariant networks are universal if high-order tensors are allowed. Second, there are groups G for which higher-order tensors are unavoidable for obtaining universality. G-invariant networks consisting of only ๏ฌrst-order tensors are of special interest due to their practical value. We conclude the paper by proving a necessary condition for the universality of G-invariant networks that incorporate only ๏ฌrst-order tensors. |
| Researcher Affiliation | Academia | 1Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel 2Department of Computer Science, University of Toronto, Toronto, Canada 3Vector Institute. Correspondence to: Haggai Maron <EMAIL>. |
| Pseudocode | No | The paper does not contain any structured pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not provide concrete access to source code for the methodology described. |
| Open Datasets | No | The paper is theoretical and does not involve training models on datasets. |
| Dataset Splits | No | The paper is theoretical and does not involve dataset splits for validation. |
| Hardware Specification | No | The paper is theoretical and does not describe any experimental setup or hardware used. |
| Software Dependencies | No | The paper is theoretical and does not list any specific software dependencies with version numbers. |
| Experiment Setup | No | The paper is theoretical and does not describe any experimental setup details such as hyperparameters or training configurations. |