Formalizing Attacker Scenarios for Adversarial Transferability
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Updated
Oct 20, 2023 - Jupyter Notebook
Formalizing Attacker Scenarios for Adversarial Transferability
A Transferability-guided Protein-Ligand Interaction Prediction Method
[ICCV2023] ETran: Energy-based Transferability Estimation
Testing whether local biodiversity estimates can be robustly predicted among similar studies
(AAAI 2024) Transferable Adversarial Attacks for Object Detection using Object-Aware Significant Feature Distortion
Multi-source Transfer Learning method for time series with Shapelet Similarity-based Source Selection implemented with Keras
Textual adversarial training with textattack
[BMVC 2023] Diversifying the High-level Features for better Adversarial Transferability
Transferability Prediction for Model Recommendation: A Graph Learning based Approach
Source of the ECCV22 paper "LGV: Boosting Adversarial Example Transferability from Large Geometric Vicinity"
Homework of Security and Privacy of Machine Learning (SPML Lectured by Shang-Tse Chen at NTU)
Our simple but effective staircase sign method which boosts the transferability of both non-targeted and targeted attacks.
Source of the UAI2022 paper "Efficient and Transferable Adversarial Examples from Bayesian Neural Networks"
Metrics to assess the generalisation ability of NILM algorithms
The extension of "Patch-wise Attack for Fooling Deep Neural Network (ECCV2020)", and we aim to boost the success rates of targeted attack.
Our Team (green hand) 6th Solution for CVPR-2021 AIC-VI: Unrestricted Adversarial Attacks on ImageNet
A Systematic Investigation of Transferability and Robustness of Humor Detection Models
SaTML 2023, 1st place in CVPR’21 Security AI Challenger: Unrestricted Adversarial Attacks on ImageNet.
Transferable Decoding with Visual Entities for Zero-Shot Image Captioning, ICCV 2023
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