| Demystifying brain tumor segmentation networks: interpretability and uncertainty analysis P Natekar, A Kori, G Krishnamurthi Frontiers in computational neuroscience 14, 6, 2020 | 82 | 2020 |
| Representation based complexity measures for predicting generalization in deep learning P Natekar, M Sharma arXiv preprint arXiv:2012.02775, 2020 | 26 | 2020 |
| Methods and analysis of the first competition in predicting generalization of deep learning Y Jiang, P Natekar, M Sharma, SK Aithal, D Kashyap, N Subramanyam, ... NeurIPS 2020 Competition and Demonstration Track, 170-190, 2021 | 22 | 2021 |
| MitoTNT: Mitochondrial Temporal Network Tracking for 4D live-cell fluorescence microscopy data Z Wang, P Natekar, C Tea, S Tamir, H Hakozaki, J Schöneberg PLoS computational biology 19 (4), e1011060, 2023 | 7 | 2023 |
| Abstracting deep neural networks into concept graphs for concept level interpretability A Kori, P Natekar, G Krishnamurthi, B Srinivasan arXiv preprint arXiv:2008.06457, 2020 | 7 | 2020 |
| Interpreting deep neural networks for medical imaging using concept graphs A Kori, P Natekar, B Srinivasan, G Krishnamurthi International Workshop on Health Intelligence, 201-216, 2021 | 6 | 2021 |
| Self-supervised deep learning uncovers the semantic landscape of drug-induced latent mitochondrial phenotypes P Natekar, Z Wang, M Arora, H Hakozaki, J Schoeneberg bioRxiv, 2023.09. 13.557636, 2023 | 1 | 2023 |
| 4D mitochondrial biophysical parameters predict cell type in human organoid tissue G McMahon, MK Rude, C Tea, Z Wang, P Natekar, H Hakozaki, ... Biophysical Journal 122 (3), 303a, 2023 | | 2023 |
Ganapathy KrishnamurthiAssociate Professor at IIT-MadrasVerified email at iitm.ac.in
