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Maram Akila
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2020 – today
- 2024
- [j5]Sujan Sai Gannamaneni, Michael Mock, Maram Akila:
Assessing systematic weaknesses of DNNs using counterfactuals. AI Ethics 4(1): 27-35 (2024) - [j4]Sergio Genovesi
, Julia Maria Mönig, Anna Schmitz, Maximilian Poretschkin, Maram Akila, Manoj Kahdan, Romina Kleiner, Lena Krieger, Alexander Zimmermann:
Standardizing fairness-evaluation procedures: interdisciplinary insights on machine learning algorithms in creditworthiness assessments for small personal loans. AI Ethics 4(2): 537-553 (2024) - [j3]Joachim Sicking
Wasserstein dropout. Mach. Learn. 113(5): 3161-3204 (2024) - [c11]Sujan Sai Gannamaneni, Frederic Klein, Michael Mock, Maram Akila:
Exploiting CLIP Self-Consistency to Automate Image Augmentation for Safety Critical Scenarios. CVPR Workshops 2024: 3594-3604 - [c10]Rebekka Görge
Inspecting and Measuring Fairness of unlabeled Image Datasets. ICDEW 2024: 191-200 - [c9]Lennard Helmer
Towards Trustworthy AI Engineering - A Case Study on integrating an AI audit catalog into MLOps processes. RAIE@ICSE 2024: 1-7 - 2023
- [j2]Elena Haedecke
ScrutinAI: A visual analytics tool supporting semantic assessments of object detection models. Comput. Graph. 114: 265-275 (2023) - [c8]Sujan Sai Gannamaneni, Arwin Sadaghiani, Rohil Prakash Rao, Michael Mock, Maram Akila:
Investigating CLIP Performance for Meta-data Generation in AD Datasets. CVPR Workshops 2023: 3840-3850 - [i12]Maximilian Poretschkin, Anna Schmitz, Maram Akila, Linara Adilova, Daniel Becker, Armin B. Cremers, Dirk Hecker, Sebastian Houben, Michael Mock, Julia Rosenzweig, Joachim Sicking, Elena Schulz, Angelika Voss, Stefan Wrobel:
Guideline for Trustworthy Artificial Intelligence - AI Assessment Catalog. CoRR abs/2307.03681 (2023) - [i11]Sujan Sai Gannamaneni, Michael Mock, Maram Akila:
Assessing Systematic Weaknesses of DNNs using Counterfactuals. CoRR abs/2308.01614 (2023) - 2022
- [j1]Anna Schmitz
The why and how of trustworthy AI. Autom. 70(9): 793-804 (2022) - [c7]Elena Haedecke
ScrutinAI: A Visual Analytics Approach for the Semantic Analysis of Deep Neural Network Predictions. EuroVA@EuroVis 2022: 1-5 - [c6]Joachim Sicking, Maximilian Pintz, Maram Akila, Tim Wirtz:
DenseHMM: Learning Hidden Markov Models by Learning Dense Representations. ICPRAM 2022: 237-248 - [i10]Joachim Sicking, Maram Akila, Jan David Schneider, Fabian Hüger, Peter Schlicht, Tim Wirtz, Stefan Wrobel:
Tailored Uncertainty Estimation for Deep Learning Systems. CoRR abs/2204.13963 (2022) - [i9]Maximilian Pintz, Joachim Sicking, Maximilian Poretschkin, Maram Akila:
A Survey on Uncertainty Toolkits for Deep Learning. CoRR abs/2205.01040 (2022) - 2021
- [c5]Julia Rosenzweig, Joachim Sicking, Sebastian Houben, Michael Mock, Maram Akila:
Patch Shortcuts: Interpretable Proxy Models Efficiently Find Black-Box Vulnerabilities. CVPR Workshops 2021: 56-65 - [c4]Linara Adilova, Elena Schulz
Plants Don't Walk on the Street: Common-Sense Reasoning for Reliable Semantic Segmentation. CVPR Workshops 2021: 85-92 - [c3]Sujan Sai Gannamaneni, Sebastian Houben, Maram Akila:
Semantic Concept Testing in Autonomous Driving by Extraction of Object-Level Annotations from CARLA. ICCVW 2021: 1006-1014 - [c2]Julia Rosenzweig, Eduardo Brito, Hans-Ulrich Kobialka, Maram Akila, Nico M. Schmidt, Peter Schlicht, Jan David Schneider, Fabian Hüger, Matthias Rottmann, Sebastian Houben, Tim Wirtz:
Validation of Simulation-Based Testing: Bypassing Domain Shift with Label-to-Image Synthesis. IV Workshops 2021: 182-189 - [i8]Joachim Sicking, Maram Akila, Maximilian Pintz, Tim Wirtz, Asja Fischer, Stefan Wrobel:
A Novel Regression Loss for Non-Parametric Uncertainty Optimization. CoRR abs/2101.02726 (2021) - [i7]Linara Adilova, Elena Schulz, Maram Akila, Sebastian Houben, Jan David Schneider, Fabian Hüger, Tim Wirtz:
Plants Don't Walk on the Street: Common-Sense Reasoning for Reliable Semantic Segmentation. CoRR abs/2104.09254 (2021) - [i6]Julia Rosenzweig, Joachim Sicking, Sebastian Houben, Michael Mock, Maram Akila:
Patch Shortcuts: Interpretable Proxy Models Efficiently Find Black-Box Vulnerabilities. CoRR abs/2104.11691 (2021) - [i5]Sebastian Houben, Stephanie Abrecht, Maram Akila, Andreas Bär, Felix Brockherde, Patrick Feifel, Tim Fingscheidt, Sujan Sai Gannamaneni, Seyed Eghbal Ghobadi, Ahmed Hammam, Anselm Haselhoff, Felix Hauser, Christian Heinzemann, Marco Hoffmann, Nikhil Kapoor, Falk Kappel, Marvin Klingner, Jan Kronenberger, Fabian Küppers, Jonas Löhdefink, Michael Mlynarski, Michael Mock, Firas Mualla, Svetlana Pavlitskaya, Maximilian Poretschkin, Alexander Pohl, Varun Ravi Kumar, Julia Rosenzweig, Matthias Rottmann, Stefan Rüping, Timo Sämann, Jan David Schneider, Elena Schulz, Gesina Schwalbe
Inspect, Understand, Overcome: A Survey of Practical Methods for AI Safety. CoRR abs/2104.14235 (2021) - [i4]Julia Rosenzweig, Eduardo Brito, Hans-Ulrich Kobialka, Maram Akila, Nico M. Schmidt, Peter Schlicht, Jan David Schneider, Fabian Hüger, Matthias Rottmann, Sebastian Houben, Tim Wirtz:
Validation of Simulation-Based Testing: Bypassing Domain Shift with Label-to-Image Synthesis. CoRR abs/2106.05549 (2021) - 2020
- [c1]Stephanie Abrecht, Maram Akila, Sujan Sai Gannamaneni, Konrad Groh, Christian Heinzemann, Sebastian Houben, Matthias Woehrle:
Revisiting Neuron Coverage and Its Application to Test Generation. SAFECOMP Workshops 2020: 289-301 - [i3]Joachim Sicking, Maram Akila, Tim Wirtz, Sebastian Houben, Asja Fischer:
Characteristics of Monte Carlo Dropout in Wide Neural Networks. CoRR abs/2007.05434 (2020) - [i2]Joachim Sicking, Maximilian Pintz, Maram Akila, Tim Wirtz:
DenseHMM: Learning Hidden Markov Models by Learning Dense Representations. CoRR abs/2012.09783 (2020) - [i1]Joachim Sicking, Maram Akila, Maximilian Pintz, Tim Wirtz, Asja Fischer, Stefan Wrobel:
Second-Moment Loss: A Novel Regression Objective for Improved Uncertainties. CoRR abs/2012.12687 (2020)
Coauthor Index
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last updated on 2024-10-11 17:30 CEST by the dblp team
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