Evaluate robustness of image processing algorithms
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Updated
Mar 2, 2019 - Python
Evaluate robustness of image processing algorithms
Finding label errors in datasets and learning with noisy labels.
Robust Effective and Resource Efficient Deep Neural networks
Robust Mini-batch Gradient Descent models
Simple math project about how designing robust and reliable paper helicopters.
This project Implements the paper “Causal Adversarial Perturbations for Individual Fairness and Robustness in Heterogeneous Data Spaces” using the Python language.
a CLI that provides a generic automation layer for assessing the security of ML models
Accompanying repository of our paper "Kamp, J., Beinborn, L., Fokkens, A. (2022). Perturbations and Subpopulations for Testing Robustness in Token-Based Argument Unit Recognition."
Desktop, Mobile and command line smart password deterministic generator
Official repository for ICLR'24 paper "Conserve-Update-Revise to Cure Generalization and Robustness Trade-off in Adversarial Training"
Defending Against Misinformation Attacks in Open-Domain Question Answering
Calculation of sensitivity coefficients and visualization
Official implementation of "Appropriate Balance of Diversification and Intensification Improves Performance and Efficiency of Adversarial Attacks", Transactions on Machine Learning Research (TMLR).
Repository for the paper "TrustLapse: An Explainable and Actionable Mistrust Scoring Framework for Model Monitoring"
measures the vulnerability of the system by formulating the aggregated metric using extended metrics.
Robustness of Sparse Multilayer Perceptrons for Supervised Feature Selection
Evaluation code for the horse-10 dataset!
TextAttack 🐙 is a Python framework for adversarial attacks, data augmentation, and model training in NLP
Characterizing Data Point Vulnerability via Average-Case Robustness, UAI 2024
[ACM MM 2021 Oral Presentation] A unified framework for co-training-based noisy label learning methods.
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