Understanding Instance-based Interpretability of Variational Auto-Encoders
Authors: Zhifeng Kong, Kamalika Chaudhuri
NeurIPS 2021 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Finally, we evaluate VAE-Trac In on several real world datasets with extensive quantitative and qualitative analysis.5 Experiments In this section, we aim to answer the following questions. Does VAE-Trac In pass a sanity check for instance-based interpretations? Which training samples have the highest and lowest self influences, respectively? Which training samples have the highest influences over (i.e. are strong proponents of) a test sample? Which have the lowest influences over it (i.e. are its strong opponents)? These questions are examined in experiments on the MNIST [Le Cun et al., 2010] and CIFAR-10 [Krizhevsky et al., 2009] datasets. |
| Researcher Affiliation | Academia | Zhifeng Kong Computer Science and Engineering University of California San Diego La Jolla, CA 92093 z4kong@eng.ucsd.edu Kamalika Chaudhuri Computer Science and Engineering University of California San Diego La Jolla, CA 92093 kamalika@cs.ucsd.edu |
| Pseudocode | No | The paper provides mathematical derivations and equations for VAE-Trac In but does not present a structured pseudocode block or algorithm. |
| Open Source Code | Yes | 3. If you ran experiments... (a) Did you include the code, data, and instructions needed to reproduce the main experimental results (either in the supplemental material or as a URL)? [Yes] We will include code in the supplemental material. |
| Open Datasets | Yes | These questions are examined in experiments on the MNIST [Le Cun et al., 2010] and CIFAR-10 [Krizhevsky et al., 2009] datasets. |
| Dataset Splits | Yes | 3. If you ran experiments... (b) Did you specify all the training details (e.g., data splits, hyperparameters, how they were chosen)? [Yes] See Appendix B.2. |
| Hardware Specification | Yes | 3. If you ran experiments... (d) Did you include the total amount of compute and the type of resources used (e.g., type of GPUs, internal cluster, or cloud provider)? [Yes] We use one NVIDIA 2080Ti GPU. |
| Software Dependencies | No | The paper mentions training details are in Appendix B.2, but does not explicitly list specific software dependencies with version numbers in the main text or the checklist provided. |
| Experiment Setup | Yes | 3. If you ran experiments... (b) Did you specify all the training details (e.g., data splits, hyperparameters, how they were chosen)? [Yes] See Appendix B.2. |