Maram Akila

Orcid: 0000-0003-0903-1439

According to our database1, Maram Akila authored at least 23 papers between 2020 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Links

On csauthors.net:

Bibliography

2024
Wasserstein dropout.
Mach. Learn., May, 2024

Standardizing fairness-evaluation procedures: interdisciplinary insights on machine learning algorithms in creditworthiness assessments for small personal loans.
AI Ethics, May, 2024

Assessing systematic weaknesses of DNNs using counterfactuals.
AI Ethics, February, 2024

Towards Trustworthy AI Engineering - A Case Study on integrating an AI audit catalog into MLOps processes.
Proceedings of the 2nd International Workshop on Responsible AI Engineering, 2024

Inspecting and Measuring Fairness of unlabeled Image Datasets.
Proceedings of the 40th International Conference on Data Engineering, ICDE 2024, 2024

Exploiting CLIP Self-Consistency to Automate Image Augmentation for Safety Critical Scenarios.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023
ScrutinAI: A visual analytics tool supporting semantic assessments of object detection models.
Comput. Graph., August, 2023

Guideline for Trustworthy Artificial Intelligence - AI Assessment Catalog.
CoRR, 2023

Investigating CLIP Performance for Meta-data Generation in AD Datasets.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022
A Survey on Uncertainty Toolkits for Deep Learning.
CoRR, 2022

Tailored Uncertainty Estimation for Deep Learning Systems.
CoRR, 2022

The why and how of trustworthy AI.
Autom., 2022

DenseHMM: Learning Hidden Markov Models by Learning Dense Representations.
Proceedings of the 11th International Conference on Pattern Recognition Applications and Methods, 2022

ScrutinAI: A Visual Analytics Approach for the Semantic Analysis of Deep Neural Network Predictions.
Proceedings of the 13th International EuroVis Workshop on Visual Analytics, 2022

2021
Inspect, Understand, Overcome: A Survey of Practical Methods for AI Safety.
CoRR, 2021

A Novel Regression Loss for Non-Parametric Uncertainty Optimization.
CoRR, 2021

Validation of Simulation-Based Testing: Bypassing Domain Shift with Label-to-Image Synthesis.
Proceedings of the IEEE Intelligent Vehicles Symposium Workshops, 2021

Semantic Concept Testing in Autonomous Driving by Extraction of Object-Level Annotations from CARLA.
Proceedings of the IEEE/CVF International Conference on Computer Vision Workshops, 2021

Patch Shortcuts: Interpretable Proxy Models Efficiently Find Black-Box Vulnerabilities.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2021

Plants Don't Walk on the Street: Common-Sense Reasoning for Reliable Semantic Segmentation.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2021

2020
Second-Moment Loss: A Novel Regression Objective for Improved Uncertainties.
CoRR, 2020

Characteristics of Monte Carlo Dropout in Wide Neural Networks.
CoRR, 2020

Revisiting Neuron Coverage and Its Application to Test Generation.
Proceedings of the Computer Safety, Reliability, and Security. SAFECOMP 2020 Workshops, 2020


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