Network Inversion of Convolutional Neural Nets (Student Abstract) Article Swipe
Pirzada Suhail
,
Amit Sethi
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1609/aaai.v39i28.35303
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1609/aaai.v39i28.35303
Neural networks have emerged as powerful tools across various applications, yet their decision-making process often remains opaque, leading to them being perceived as "black boxes." This opacity raises concerns about their interpretability and reliability, especially in safety-critical scenarios. Network inversion techniques offer a solution by allowing us to peek inside these black boxes, revealing the features and patterns learned by the networks behind their decision-making processes and thereby provide valuable insights into how neural networks arrive at their conclusions, making them more interpretable and trustworthy. This paper presents a simple yet effective approach to network inversion using a meticulously conditioned generator that learns the data distribution in the input space of the trained neural network, enabling the reconstruction of inputs that would most likely lead to the desired outputs. To capture the diversity in the input space for a given output, instead of simply revealing the conditioning labels to the generator, we encode the conditioning label information into vectors and intermediate matrices and further minimize the cosine similarity between features of the generated images.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1609/aaai.v39i28.35303
- https://ojs.aaai.org/index.php/AAAI/article/download/35303/37458
- OA Status
- diamond
- References
- 8
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4409381819
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4409381819Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1609/aaai.v39i28.35303Digital Object Identifier
- Title
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Network Inversion of Convolutional Neural Nets (Student Abstract)Work title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2025Year of publication
- Publication date
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2025-04-11Full publication date if available
- Authors
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Pirzada Suhail, Amit SethiList of authors in order
- Landing page
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https://doi.org/10.1609/aaai.v39i28.35303Publisher landing page
- PDF URL
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https://ojs.aaai.org/index.php/AAAI/article/download/35303/37458Direct link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
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diamondOpen access status per OpenAlex
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https://ojs.aaai.org/index.php/AAAI/article/download/35303/37458Direct OA link when available
- Concepts
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Convolutional neural network, Inversion (geology), Computer science, Artificial intelligence, Geology, Seismology, TectonicsTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
- References (count)
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8Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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