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Durability of assemblies : a study on load transfer in bolted joints
Adeline Fau
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Learning potential energy surfaces of hydrogen atom transfer reactions in peptides.
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The International Journal of Psychoanalysis, 2023
The article presents a view of transference from the early versions of transference by Classical/Structural analysts, through a variety of analytic positions that extend and implicitly question the concept of transference. After looking at Brenner and Bird's transference positions, we trace the beginning of relational analysis as articulated by Gill ...
Steven, Ellman, Lissa, Weinstein
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The article presents a view of transference from the early versions of transference by Classical/Structural analysts, through a variety of analytic positions that extend and implicitly question the concept of transference. After looking at Brenner and Bird's transference positions, we trace the beginning of relational analysis as articulated by Gill ...
Steven, Ellman, Lissa, Weinstein
openaire +2 more sources
A Survey on Transferability of Adversarial Examples across Deep Neural Networks
Trans. Mach. Learn. Res., 2023The emergence of Deep Neural Networks (DNNs) has revolutionized various domains by enabling the resolution of complex tasks spanning image recognition, natural language processing, and scientific problem-solving.
Jindong Gu +11 more
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IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021
Unsupervised domain adaptation without accessing expensive annotation processes of target data has achieved remarkable successes in semantic segmentation.
Jiahua Dong +4 more
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Unsupervised domain adaptation without accessing expensive annotation processes of target data has achieved remarkable successes in semantic segmentation.
Jiahua Dong +4 more
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Improving the Transferability of Adversarial Samples with Adversarial Transformations
Computer Vision and Pattern Recognition, 2021Although deep neural networks (DNNs) have achieved tremendous performance in diverse vision challenges, they are surprisingly susceptible to adversarial examples, which are born of intentionally perturbing benign samples in a human-imperceptible fashion.
Weibin Wu, Yuxin Su, M. Lyu, Irwin King
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