Srishti Gautam

According to our database, Srishti Gautam authored at least 14 papers between 2017 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Prototypical Self-Explainable Models Without Re-training.

Srishti Gautam, Ahcene Boubekki, Marina M.-C. Höhne, Michael Kampffmeyer

Trans. Mach. Learn. Res., 2024

Confronting LLMs with Traditional ML: Rethinking the Fairness of Large Language Models in Tabular Classifications.

Yanchen Liu, Srishti Gautam, Jiaqi Ma, Himabindu Lakkaraju

Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), 2024

2023

ADNet++: A few-shot learning framework for multi-class medical image volume segmentation with uncertainty-guided feature refinement.

Stine Hansen, Srishti Gautam, Suaiba Amina Salahuddin, Michael Kampffmeyer, Robert Jenssen

Medical Image Anal., October, 2023

<i>This</i> looks <i>More</i> Like <i>that</i>: Enhancing Self-Explaining Models by Prototypical Relevance Propagation.

Srishti Gautam, Marina M.-C. Höhne, Stine Hansen, Robert Jenssen, Michael Kampffmeyer

Pattern Recognit., April, 2023

Investigating the Fairness of Large Language Models for Predictions on Tabular Data.

Yanchen Liu, Srishti Gautam, Jiaqi Ma, Himabindu Lakkaraju

CoRR, 2023

2022

Anomaly detection-inspired few-shot medical image segmentation through self-supervision with supervoxels.

Stine Hansen, Srishti Gautam, Robert Jenssen, Michael Kampffmeyer

Medical Image Anal., 2022

ProtoVAE: A Trustworthy Self-Explainable Prototypical Variational Model.

Srishti Gautam, Ahcène Boubekki, Stine Hansen, Suaiba Amina Salahuddin, Robert Jenssen, Marina M.-C. Höhne, Michael Kampffmeyer

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Demonstrating the Risk of Imbalanced Datasets in Chest X-Ray Image-Based Diagnostics by Prototypical Relevance Propagation.

Srishti Gautam, Marina M.-C. Höhne, Stine Hansen, Robert Jenssen, Michael Kampffmeyer

Proceedings of the 19th IEEE International Symposium on Biomedical Imaging, 2022

A self-guided anomaly detection-inspired few-shot segmentation network.

Suaiba Amina Salahuddin, Stine Hansen, Srishti Gautam, Michael Kampffmeyer, Robert Jenssen

Proceedings of the Colour and Visual Computing Symposium 2022, 2022

2021

This looks more like that: Enhancing Self-Explaining Models by Prototypical Relevance Propagation.

Srishti Gautam, Marina M.-C. Höhne, Stine Hansen, Robert Jenssen, Michael Kampffmeyer

CoRR, 2021

2018

Considerations for a PAP Smear Image Analysis System with CNN Features.

Srishti Gautam, Harinarayan K. K., O. U. Nirmal Jith, Anil Kumar Sao, Arnav Bhavsar, Adarsh Natarajan

CoRR, 2018

CNN based segmentation of nuclei in PAP-smear images with selective pre-processing.

Srishti Gautam, Arnav Bhavsar, Anil Kumar Sao, Harinarayan K. K.

Proceedings of the Medical Imaging 2018: Digital Pathology, 2018

DeepCerv: Deep Neural Network for Segmentation Free Robust Cervical Cell Classification.

O. U. Nirmal Jith, K. K. Harinarayanan, Srishti Gautam, Arnav Bhavsar, Anil Kumar Sao

Proceedings of the Computational Pathology and Ophthalmic Medical Image Analysis, 2018

2017

Unsupervised Segmentation of Cervical Cell Nuclei via Adaptive Clustering.

Srishti Gautam, Krati Gupta, Arnav Bhavsar, Anil Kumar Sao

Proceedings of the Medical Image Understanding and Analysis - 21st Annual Conference, 2017