# Secure and transparent artificial intelligence through uncertainty-infused algebraic frameworks

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/secure-and-transparent-artificial-intelligence-through-uncertainty-infused/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Bagesh Kumar,Jeba Nega Cheltha,Praveen Kumar Yadav,Manish Kumar Sharma,Pankaj Dadheech,Shyam Sunder Manaktala |
| Citations | 0 |
| DOI | 10.47974/jdmsc-2652 |
| Fields | Computer Science |
| Open Access | false |
| OA Status | closed |
| OpenAlex ID | https://openalex.org/W7130504893 |
| Type | article |
| Year | 2026 |

## Paper authors

- [Jeba Nega Cheltha](https://scholariq.org/researchers/jeba-nega-cheltha/)

## Paper journal

- [Journal of Discrete Mathematical Sciences and Cryptography](https://scholariq.org/journals/journal-of-discrete-mathematical-sciences-and-cryptography/)

## Paper primary topic

- [Advanced Graph Neural Networks](https://scholariq.org/topics/advanced-graph-neural-networks/)

## Paper topics

- [Advanced Graph Neural Networks](https://scholariq.org/topics/advanced-graph-neural-networks/)
- [Explainable Artificial Intelligence (XAI)](https://scholariq.org/topics/explainable-artificial-intelligence-xai/)
- [Adversarial Robustness in Machine Learning](https://scholariq.org/topics/adversarial-robustness-in-machine-learning/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.