Demystifying Brain Tumour Segmentation Networks: Interpretability and Uncertainty Analysis. - Parth Natekar; Avinash Kori; Ganapathy Krishnamurthi (CoRR, 2019)

Methods and Analysis of The First Competition in Predicting Generalization of Deep Learning. - Yiding Jiang; Parth Natekar; Manik Sharma; Sumukh K. Aithal; Dhruva Kashyap; Natarajan Subramanyam; Carlos Lassance; Daniel M. Roy 001; Gintare Karolina Dziugaite; Suriya Gunasekar; Isabelle Guyon; Pierre Foret; et al. (NeurIPS (Competition and Demos), 2020)

Abstracting Deep Neural Networks into Concept Graphs for Concept Level Interpretability. - Avinash Kori; Parth Natekar; Ganapathy Krishnamurthi; Balaji Srinivasan (CoRR, 2020)

Representation Based Complexity Measures for Predicting Generalization in Deep Learning. - Parth Natekar; Manik Sharma (CoRR, 2020)

Demystifying Brain Tumor Segmentation Networks: Interpretability and Uncertainty Analysis. - Parth Natekar; Avinash Kori; Ganapathy Krishnamurthi (Frontiers Comput. Neurosci., 2020)

Corrigendum: Demystifying Brain Tumor Segmentation Networks: Interpretability and Uncertainty Analysis. - Parth Natekar; Avinash Kori; Ganapathy Krishnamurthi (Frontiers Comput. Neurosci., 2021)

MitoTNT: Mitochondrial Temporal Network Tracking for 4D live-cell fluorescence microscopy data. - Zichen Wang; Parth Natekar; Challana Tea; Sharon Tamir; Hiroyuki Hakozaki; Johannes Schöneberg (PLoS Comput. Biol., 2023)