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2020 – today
- 2024
[c4]Vidhya Kamakshi
, Narayanan C. Krishnan:
SCE: Shared Concept Extractor to Explain a CNN's Classification Dynamics. COMAD/CODS 2024: 109-117- 2022
- [c3]Vidhya Kamakshi, Narayanan C. Krishnan:
Explainable Supervised Domain Adaptation. IJCNN 2022: 1-8 - 2021
- [j1]Ashish Kumar, Karan Sehgal, Prerna Garg, Vidhya Kamakshi, Narayanan Chatapuram Krishnan:
MACE: Model Agnostic Concept Extractor for Explaining Image Classification Networks. IEEE Trans. Artif. Intell. 2(6): 574-583 (2021) - [c2]Rajat Sharma, Nikhil Reddy, Vidhya Kamakshi, Narayanan C. Krishnan, Shweta Jain:
MAIRE - A Model-Agnostic Interpretable Rule Extraction Procedure for Explaining Classifiers. CD-MAKE 2021: 329-349 - [c1]Vidhya Kamakshi, Uday Gupta, Narayanan C. Krishnan:
PACE: Posthoc Architecture-Agnostic Concept Extractor for Explaining CNNs. IJCNN 2021: 1-8 - [i4]Sam Zabdiel Sunder Samuel, Vidhya Kamakshi, Namrata Lodhi, Narayanan C. Krishnan:
Evaluation of Saliency-based Explainability Method. CoRR abs/2106.12773 (2021) - [i3]Vidhya Kamakshi, Uday Gupta, Narayanan C. Krishnan:
PACE: Posthoc Architecture-Agnostic Concept Extractor for Explaining CNNs. CoRR abs/2108.13828 (2021) - 2020
- [i2]Ashish Kumar, Karan Sehgal, Prerna Garg, Vidhya Kamakshi, Narayanan C. Krishnan:
MACE: Model Agnostic Concept Extractor for Explaining Image Classification Networks. CoRR abs/2011.01472 (2020) - [i1]Rajat Sharma, Nikhil Reddy, Vidhya Kamakshi, Narayanan C. Krishnan, Shweta Jain:
MAIRE - A Model-Agnostic Interpretable Rule Extraction Procedure for Explaining Classifiers. CoRR abs/2011.01506 (2020)
Coauthor Index
aka: Narayanan C. Krishnan
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