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..
Expressivity of ReLU-Networks under Convex Relaxations
Authors: Maximilian Baader, Mark Niklas Mueller, Yuhao Mao, Martin Vechev
ICLR 2024 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | In this work, we prove the following key results: |
| Researcher Affiliation | Academia | Department of Computer Science ETH Zurich, Switzerland EMAIL |
| Pseudocode | No | The paper contains mathematical derivations, lemmas, and theorems, but no explicitly labeled pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not contain any explicit statements or links regarding the availability of open-source code for the described methodology. |
| Open Datasets | No | This paper is theoretical, focusing on mathematical proofs and expressivity. It does not conduct experiments using datasets, and thus provides no information about public dataset availability. |
| Dataset Splits | No | As a theoretical paper, it does not involve data splits for training, validation, or testing. |
| Hardware Specification | No | The paper is theoretical and does not describe any experiments that would require specific hardware for execution. |
| Software Dependencies | No | The paper focuses on theoretical concepts and mathematical proofs and does not specify software dependencies with version numbers. |
| Experiment Setup | No | As a theoretical paper, it does not include details on experimental setup, hyperparameters, or training configurations. |