Srishti Gautam

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 18

Top Topics

Imbalanced Datasets

Confocal Images

Image Segmentation

Top Venues

Medical Image Anal.

Pattern Recognit.

Publications

Yanchen Liu, Srishti Gautam, Jiaqi Ma, Himabindu Lakkaraju
Confronting LLMs with Traditional ML: Rethinking the Fairness of Large Language Models in Tabular Classifications. NAACL-HLT (2024)
Srishti Gautam, Ahcene Boubekki, Marina M.-C. Höhne, Michael Kampffmeyer
Prototypical Self-Explainable Models Without Re-training. Trans. Mach. Learn. Res. 2024 (2024)
Yanchen Liu, Srishti Gautam, Jiaqi Ma, Himabindu Lakkaraju
Investigating the Fairness of Large Language Models for Predictions on Tabular Data. CoRR (2023)
Srishti Gautam, Marina M.-C. Höhne, Stine Hansen, Robert Jenssen, Michael Kampffmeyer
: Enhancing Self-Explaining Models by Prototypical Relevance Propagation. Pattern Recognit. 136 (2023)
Srishti Gautam, Ahcene Boubekki, Marina M.-C. Höhne, Michael C. Kampffmeyer
Prototypical Self-Explainable Models Without Re-training. CoRR (2023)
Stine Hansen, Srishti Gautam, Suaiba Amina Salahuddin, Michael Kampffmeyer, Robert Jenssen
ADNet++: A few-shot learning framework for multi-class medical image volume segmentation with uncertainty-guided feature refinement. Medical Image Anal. 89 (2023)
Srishti Gautam, Marina M.-C. Höhne, Stine Hansen, Robert Jenssen, Michael Kampffmeyer
Demonstrating the Risk of Imbalanced Datasets in Chest X-Ray Image-Based Diagnostics by Prototypical Relevance Propagation. ISBI (2022)
Stine Hansen, Srishti Gautam, Robert Jenssen, Michael Kampffmeyer
Anomaly Detection-Inspired Few-Shot Medical Image Segmentation Through Self-Supervision With Supervoxels. CoRR (2022)
Stine Hansen, Srishti Gautam, Robert Jenssen, Michael Kampffmeyer
Anomaly detection-inspired few-shot medical image segmentation through self-supervision with supervoxels. Medical Image Anal. 78 (2022)
Srishti Gautam, Marina M.-C. Höhne, Stine Hansen, Robert Jenssen, Michael Kampffmeyer
Demonstrating The Risk of Imbalanced Datasets in Chest X-ray Image-based Diagnostics by Prototypical Relevance Propagation. CoRR (2022)
Srishti Gautam, Ahcene Boubekki, Stine Hansen, Suaiba Amina Salahuddin, Robert Jenssen, Marina M.-C. Höhne, Michael Kampffmeyer
ProtoVAE: A Trustworthy Self-Explainable Prototypical Variational Model. CoRR (2022)
Suaiba Amina Salahuddin, Stine Hansen, Srishti Gautam, Michael Kampffmeyer, Robert Jenssen
A self-guided anomaly detection-inspired few-shot segmentation network. CVCS (2022)
Srishti Gautam, Ahcène Boubekki, Stine Hansen, Suaiba Amina Salahuddin, Robert Jenssen, Marina M.-C. Höhne, Michael Kampffmeyer
ProtoVAE: A Trustworthy Self-Explainable Prototypical Variational Model. NeurIPS (2022)
Srishti Gautam, Marina M.-C. Höhne, Stine Hansen, Robert Jenssen, Michael Kampffmeyer
This looks more like that: Enhancing Self-Explaining Models by Prototypical Relevance Propagation. CoRR (2021)
Srishti Gautam, Arnav Bhavsar, Anil Kumar Sao, Harinarayan K. K.
CNN based segmentation of nuclei in PAP-smear images with selective pre-processing. Medical Imaging: Digital Pathology (2018)
Srishti Gautam, Harinarayan K. K., O. U. Nirmal Jith, Anil Kumar Sao, Arnav Bhavsar, Adarsh Natarajan
Considerations for a PAP Smear Image Analysis System with CNN Features. CoRR (2018)
O. U. Nirmal Jith, K. K. Harinarayanan, Srishti Gautam, Arnav Bhavsar, Anil Kumar Sao
DeepCerv: Deep Neural Network for Segmentation Free Robust Cervical Cell Classification. COMPAY/OMIA@MICCAI (2018)
Srishti Gautam, Krati Gupta, Arnav Bhavsar, Anil Kumar Sao
Unsupervised Segmentation of Cervical Cell Nuclei via Adaptive Clustering. MIUA (2017)