robustness
an archive of posts in this category
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Stability Analysis of Sharpness-Aware Minimization
연구실 논문 소개: 인공지능 일반화
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Adversarial Training for Free!
Adversarial Robustness 논문 세미나 자료
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Adversarial Training for Free!
Adversarial Robustness Paper Seminar Materials
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Adversarial Examples Are Not Bugs, They Are Features
Adversarial Robustness 논문 세미나 자료
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Adversarial Examples Are Not Bugs, They Are Features
Adversarial Robustness Paper Seminar Materials reinterpreting adversarial examples as non-robust features learned from data.
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Theoretically Principled Trade-off between Robustness and Accuracy
Adversarial Robustness 논문 세미나 자료
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Theoretically Principled Trade-off between Robustness and Accuracy
Adversarial Robustness Paper Seminar Materials
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Robustness May Be at Odds with Accuracy
Adversarial Robustness 논문 세미나 자료
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Robustness May Be at Odds with Accuracy
Adversarial Robustness Paper Seminar Materials
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Code Review: Adversarial Attacks and Defenses
torchattacks · MAIR 라이브러리 기반 적대적 공격·방어 기법 코드 리뷰
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Code Review: Adversarial Attacks and Defenses
Line-by-line PyTorch walkthrough of torchattacks and MAIR implementations of adversarial attacks and defenses.
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Towards Evaluating the Robustness of Neural Networks
Adversarial Robustness 논문 세미나 자료
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Towards Evaluating the Robustness of Neural Networks
C&W attacks expose that defensive distillation only masked existing attack weaknesses, redefining how adversarial robustness is evaluated.
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Obfuscated Gradients Give a False Sense of Security
Adversarial Robustness 논문 세미나 자료
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Obfuscated Gradients Give a False Sense of Security
Adversarial Robustness Paper Seminar Materials
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Adversarial Examples in the Physical World
Adversarial Robustness 논문 세미나 자료
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Adversarial Examples in the Physical World
Adversarial Robustness Paper Seminar Material
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Towards Deep Learning Models Resistant to Adversarial Attacks
Adversarial Robustness 논문 세미나 자료
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Towards Deep Learning Models Resistant to Adversarial Attacks
Adversarial Robustness paper seminar material
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Intriguing Properties of Neural Networks
Adversarial Robustness 논문 세미나 자료
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Intriguing Properties of Neural Networks
Adversarial Robustness Paper Seminar Material
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Explaining and Harnessing Adversarial Examples
Adversarial Robustness 논문 세미나 자료
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Explaining and Harnessing Adversarial Examples
Adversarial Robustness paper seminar material
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인공지능 위협과 신뢰성
본 연구실이 제안하는 인공지능 위협의 두 층위(내재적 위협, 외재적 위협)와 신뢰성을 확보하기 위한 핵심 요소 및 국내외 규제 동향
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AI Threat and Trustworthiness
The two layers of AI threats that our lab proposes (intrinsic and extrinsic), and the key elements and regulations needed to make AI trustworthy
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Evaluating Practical Adversarial Robustness of Fault Diagnosis Systems via Spectrogram-Aware Ensemble Method
연구실 논문 소개: 인공지능 강건성
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Evaluating Practical Adversarial Robustness of Fault Diagnosis Systems via Spectrogram-Aware Ensemble Method
Lab paper introduction: AI robustness
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신뢰할 수 있는 인공지능의 핵심 요소와 기술적 과제
신뢰할 수 있는 인공지능의 개념 및 연구실의 주요 기술 소개
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Key Elements and Technical Challenges of Trustworthy AI
Concepts of trustworthy AI and introduction to our lab's key technologies
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인공지능 규제와 신뢰성
국제·국내 인공지능 관련 규제와 인공지능 신뢰성
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AI Regulations and Trustworthiness
International and domestic AI-related regulations and AI trustworthiness
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Fantastic Robustness Measures: The Secrets of Robust Generalization
연구실 논문 소개: 인공지능 강건성
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Fantastic Robustness Measures: The Secrets of Robust Generalization
Adversarial robustness and the recent research paper from our lab