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Srishti Gautam
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2020 – today
- 2024
- [j4]Srishti Gautam, Ahcene Boubekki, Marina M.-C. Höhne, Michael Kampffmeyer:
Prototypical Self-Explainable Models Without Re-training. Trans. Mach. Learn. Res. 2024 (2024) - [c7]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: 3603-3620 - 2023
- [j3]Stine Hansen
, Srishti Gautam
ADNet++: A few-shot learning framework for multi-class medical image volume segmentation with uncertainty-guided feature refinement. Medical Image Anal. 89: 102870 (2023) - [j2]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. Pattern Recognit. 136: 109172 (2023) - [i7]Yanchen Liu, Srishti Gautam, Jiaqi Ma, Himabindu Lakkaraju:
Investigating the Fairness of Large Language Models for Predictions on Tabular Data. CoRR abs/2310.14607 (2023) - [i6]Srishti Gautam, Ahcene Boubekki, Marina M.-C. Höhne, Michael C. Kampffmeyer:
Prototypical Self-Explainable Models Without Re-training. CoRR abs/2312.07822 (2023) - 2022
- [j1]Stine Hansen
Anomaly detection-inspired few-shot medical image segmentation through self-supervision with supervoxels. Medical Image Anal. 78: 102385 (2022) - [c6]Suaiba Amina Salahuddin, Stine Hansen, Srishti Gautam, Michael Kampffmeyer, Robert Jenssen:
A self-guided anomaly detection-inspired few-shot segmentation network. CVCS 2022 - [c5]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: 1-5 - [c4]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 - [i5]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 abs/2201.03559 (2022) - [i4]Stine Hansen, Srishti Gautam, Robert Jenssen, Michael Kampffmeyer:
Anomaly Detection-Inspired Few-Shot Medical Image Segmentation Through Self-Supervision With Supervoxels. CoRR abs/2203.02048 (2022) - [i3]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 abs/2210.08151 (2022) - 2021
- [i2]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 abs/2108.12204 (2021)
2010 – 2019
- 2018
- [c3]O. U. Nirmal Jith, K. K. Harinarayanan, Srishti Gautam, Arnav Bhavsar
DeepCerv: Deep Neural Network for Segmentation Free Robust Cervical Cell Classification. COMPAY/OMIA@MICCAI 2018: 86-94 - [c2]Srishti Gautam, Arnav Bhavsar
CNN based segmentation of nuclei in PAP-smear images with selective pre-processing. Digital Pathology 2018: 105810X - [i1]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 abs/1806.09025 (2018) - 2017
- [c1]Srishti Gautam, Krati Gupta, Arnav Bhavsar
Unsupervised Segmentation of Cervical Cell Nuclei via Adaptive Clustering. MIUA 2017: 815-826
Coauthor Index
aka: Michael C. Kampffmeyer
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