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 Incorporating Inductive Biases into VAEs
Authors: Ning Miao, Emile Mathieu, Siddharth N, Yee Whye Teh, Tom Rainforth
ICLR 2022 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Experimental results show their superiority compared with baseline methods in both generation and feature quality, most notably providing state-of-the-art performance for learning sparse representations in the VAE framework. |
| Researcher Affiliation | Academia | 1Department of Statistics, University of Oxford, 2University of Edinburgh |
| Pseudocode | No | The paper describes the computational steps and formulas, but does not contain a structured pseudocode or algorithm block that is clearly labeled as such. |
| Open Source Code | Yes | Accompanying code is provided at https://github.com/Ning Miao/Inte L-VAE. |
| Open Datasets | Yes | For real datasets, We load MNIST, Fashion-MNIST, and Celeb A directly from Tensorflow (Abadi et al., 2015) |
| Dataset Splits | Yes | Dataset sizes Unlimited 55k/5k/10k 55k/5k/10k 10k/1k/2k 163k/20k/20k Input space R2 Binary 28x28 Binary 28x28 Binary 28x28 RGB 64x64x3 |
| Hardware Specification | Yes | All experiments are run on a GTX-1080-Ti GPU. |
| Software Dependencies | No | The paper mentions using 'Tensorflow' but does not provide specific version numbers for it or any other key software dependencies or libraries used in the experiments. |
| Experiment Setup | Yes | Table C.1: Hyperparameters used for different experiments. This table specifies 'Batch size', 'Optimizer Adam', and 'Learning rate'. |