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..
Sensory Integration and Density Estimation
Authors: Joseph G Makin, Philip N. Sabes
NeurIPS 2014 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | We prove here an analytical connection between these seemingly different tasks, density estimation and sensory integration; that the former implies the latter for the model used in [2]; but that this does not appear to be true for all models. and Here we prove analytically that successful density estimation in certain models, including that of [2], will necessarily satisfy the information-retention criterion. |
| Researcher Affiliation | Academia | Joseph G. Makin and Philip N. Sabes Center for Integrative Neuroscience/Department of Physiology University of California, San Francisco San Francisco, CA 94143-0444 USA makin, sabes @phy.ucsf.edu |
| Pseudocode | No | The paper does not contain any pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not provide an explicit statement or link for the open-sourcing of code related to the analytical proof presented in this paper. |
| Open Datasets | No | The paper describes data generation for related empirical work but does not provide access information (link, DOI, or explicit public dataset name with citation) for a dataset used in its own analysis. |
| Dataset Splits | No | The paper is theoretical and does not perform experiments requiring training, validation, or test splits. |
| Hardware Specification | No | The paper is theoretical and does not describe experimental hardware specifications. |
| Software Dependencies | No | The paper does not list specific software dependencies with version numbers for its analytical work. |
| Experiment Setup | No | The paper is theoretical and does not describe an experimental setup with hyperparameter values or training configurations. |