Explaining Deep Neural Network Models with Adversarial Gradient Integration
Authors: Deng Pan, Xin Li, Dongxiao Zhu
IJCAI 2021 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | In this section, we perform experiments attempting to answer the following questions: 1) does AGI output meaningful interpretations for classifying the true class? 2) does class subsampling compromise the performance? 3) does individual AGI give reasonable interpretation for discriminating the true class against a false class? and 4) does AGI pass sanity checks. All experiments are conducted using Image Net dataset. |
| Researcher Affiliation | Academia | Deng Pan , Xin Li and Dongxiao Zhu Department of Computer Science, Wayne State University, USA {pan.deng, xinlee, dzhu}@wayne.edu |
| Pseudocode | Yes | Algorithm 1: Individual AGI(f, x, i, ϵ, m) and Algorithm 2: AGI(f, x, ϵ, k, m) are presented. |
| Open Source Code | Yes | Code is available from https://github.com/pd90506/AGI. |
| Open Datasets | Yes | All experiments are conducted using Image Net dataset. |
| Dataset Splits | No | The paper mentions evaluating on "1000 test examples" from ImageNet, but it does not specify the training or validation split percentages or absolute sample counts for each split. It relies on pre-trained models rather than training models from scratch with explicit splits. |
| Hardware Specification | Yes | For Inception V3, setting the max ascending step = 20, and sample size = 20, it will cost 15 seconds to interpret a single 224 224 color image on a computer with Nvidia GTX 1080 GPU. |
| Software Dependencies | No | The paper does not provide specific version numbers for any software dependencies (e.g., programming languages, libraries, or frameworks). |
| Experiment Setup | Yes | Regarding parameter settings, we set the step size ϵ = 0.05, and the class subsampling size for Image Net to 20. For Inception V3, setting the max ascending step = 20, and sample size = 20 |